Minimizing spatial and time reservation with Collision-Aware DCF in mobile ad hoc networks

Transcription

1 Available online at Ad Hoc Netwoks 7 (29) Minimizing spatial and time esevation with Collision-Awae DCF in mobile ad hoc netwoks Lubo Song a, Chansu Yu b, * a Telephony Softwae Development Technology Division, Palm, Inc., 95 W. Maude Avenue, Sunnyvale, CA 9485, United States b Depatment of Electical and Compute Engineeing, Cleveland State Univesity, 2121 Euclid Avenue, Stilwell Hall 437, Cleveland, OH 44115, United States Received 6 Novembe 26; eceived in evised fom 26 July 27; accepted 4 Febuay 28 Available online 15 Febuay 28 Abstact Caie sensing is widely adopted in wieless communication to potect data tansfes fom collisions. Fo example, distibuted coodination function (DCF) in IEEE standad endes a node to defe its communication if it senses the medium busy. Fo the duation of defement, each fame caies, in its MAC heade, a 16-bit numbe in micoseconds duing which any oveheaing node must defe. Howeve, even if the caie signal is detected, both ongoing and a new communication can be simultaneously successful depending on thei elative positions in the netwok o equivalently, thei mutual intefeence level. Suppoting multiple concuent communications is impotant in multihop ad hoc netwoks in ode to maximize the netwok pefomance. Howeve, it is lagely ignoed in DCF of the standads because it is pimaily tageted at single-hop wieless LANs. In addition, in DCF, the time duation infomation mentioned above is not deliveed to all potential intefees, paticulaly those in the distance. This pape poposes Collision-Awae DCF (CAD) that efficiently utilizes the available channel esouce along with the spatial as well as time dimension. Fist, each node makes its defement decision adaptively based on the feedback fom the communication countepat and the status of the medium athe than on a simple, fixed caie sense theshold as DCF. Second, CAD embeds the spatial and time esevation equiements in the PHY heade, which is tansmitted at the lowest data ate, so that a lage goup of neighbos become awae of the ongoing communication and thus avoid collisions. Extensive expeiments based on ns-2 netwok simulato show that CAD consistently outpefoms DCF egadless of node mobility, taffic intensity, and channel andomness. Fo pacticality, this pape discusses the implementation of CAD based on the DCF specification. Ó 28 Elsevie B.V. All ights eseved. Keywods: Caie sense multiple access (CSMA); Mobile ad hoc netwoks (MANETs); Distibuted coodination function (DCF); Popagation model; Spatial euse 1. Intoduction * Coesponding autho. Tel.: addesses: lubo.song@palm.com (L. Song), c.yu91@ csuohio.edu (C. Yu). Wieless LANs (WLANs) based on IEEE standads [1] ae in geat populaity in public as well as in esidential aeas offeing new level of infomation accessibility and convenience of life. This tend /$ - see font matte Ó 28 Elsevie B.V. All ights eseved. doi:1.116/j.adhoc

2 L. Song, C. Yu / Ad Hoc Netwoks 7 (29) enables the netwok inteface cad available at an affodable pice making it feasible to equip additional featues such as tansmit powe and tansmit ate contol [2]. Howeve, WLAN hadwae as well as the undelying standads has been oiginally developed fo single-hop wieless communications between an access point (AP) and end clients, which may not be appopiate fo multihop communications. As vaious foms of multihop netwoks such as wieless mesh netwoks [3,4] and wieless senso netwoks [5,6] emege, it is citically impotant to econside design choices made fo WLANs in the context of multihop envionment. Fo example, Ramanathan ecently discussed thee key aeas of econsideation fo mobile ad hoc netwoks (MANETs) [7]: Relay communication pimitive in addition to tansmit and eceive pimitives, path-centic medium access athe than hopcentic, and coopeative tanspot of data fames. In this context, this pape poposes an efficient medium access contol (MAC) mechanism optimized fo multihop envionment. Moe specifically, this pape claims that caie sense (CS)-based MAC algoithm such as distibuted coodination function (DCF) of IEEE standad [1] does not efficiently utilize the spatial spectal esouce in MANETs. Accoding to the DCF, a node needs to defe its tansmission if it obseves the caie signal above the pe-specified CS theshold [8]. Since thee exists at most one communication in WLANs, it is beneficial to set the CS theshold as low as possible in ode to peclude as many othe communication attempts as possible and thus to potect the ongoing communication. This must be contasted to multihop envionment, the essential idea of which is to suppot multiple concuent communications fo the efficient use of the limited spectal esouce. A low CS theshold is not desiable because it disallows moe communications than necessay and degades the netwok pefomance. On the othe hand, a high CS theshold may cause moe collisions by encouaging moe concuent communications. Finding a tadeoff between the spatial euse and collision has been an active eseach aea in ecent yeas [9 13]. Ou goal in this pape is to develop a distibuted MAC algoithm, called Collision-Awae DCF (CAD), whee each node adjusts the CS theshold of its adio just enough to potect the ongoing communication. It essentially eseves the smallest spatial aea and thus allows othe nodes to initiate the tansmission of thei pending fames. In othe wods, CAD povides moe tansmission oppotunities than DCF by eliminating unnecessay tansmission defeals and thus helps incease the spatial spectal utilization leading to a highe netwok thoughput. Fo instance, when the sende and the eceive ae sufficiently nea with each othe, thei communication would be successful even in the pesence of intefeence because signal-to-noise-intefeence atio (SINR) at the eceive is high anyway [14]. Theefoe, any additional communication in the neighbohood would not be a poblem even though both tansmittes ae within each othe s caie sense aea. In CAD, each tansmitte estimates the spatial esevation equiement fo its data tansfe and shaes this infomation with its neighbos by piggybacking it in contol and data fames. It makes it possible fo the neighbos to speculate on whethe thei data tansfe would intefee o be intefeed by ongoing communication. Contibutions of this pape ae thee-fold: Fist, this pape highlights the impotance of efficient use of spatial esouce in multihop envionment. It poposes CAD whee each communication expenses the smallest necessay spatial aea fo the least amount of time and thus the oveall netwok thoughput can be maximized. Second, CAD is a coopeative scheme in the sense that each node makes its defement decision based not only on its own equiements but also on the collective infomation fom nodes in the neighbohood. Consideing the distibuted natue of multihop envionment, coopeation among the nodes is a necessity in optimizing the netwok pefomance. We hope this wok facilitates futue eseach on MANETs in this diection. Thid, anothe unique featue of CAD is that the esevation equiements ae embedded in the physical (PHY) heade (called physical laye convegence potocol (PLCP) heade in teminologies) athe than in the MAC heade as explained in Section 4. Since the PLCP heade is usually tansmitted at the basic, lowest ate, this guaantees that the infomation is popagated to a lage goup of neighbos leading to a moe efficient use of the spatial esouce. To the best of the authos knowledge, thee has been no such study in the liteatue. A caveat is that the CAD potocol equies incompatible changes to the DCF because of the additional fields in the PLCP heade. Howeve, as discussed

3 232 L. Song, C. Yu / Ad Hoc Netwoks 7 (29) ealie, we believe that multihop netwoking demands new designs in many espects and hope the poposed changes in this pape would be consideed fo adopting in futue WLAN standads fo MANETs. The est of the pape is oganized as follows. Section 2 summaizes techniques that impove the spatial eusability in multihop ad hoc netwoks. Section 3 pesents system model including signal popagation model and IEEE DCF. The poposed algoithm, CAD, is intoduced in Section 4. Section 5 demonstates the pefomance benefits of CAD via ns-2 simulation. Finally Section 6 daws conclusions and descibes the futue wok of this study. 2. Related wok In MANETs, spatial aea is one of the valuable esouces. Impoving the spatial eusability takes moe impotance as wieless bandwidth is citically limited, paticulaly in unlicensed ISM bands. This section summaizes ecent wok addessing this issue based on tansmit powe contol (TPC), tansmit ate contol (TRC), diectional antenna contol (DAC) and caie sense contol (CSC) techniques A tansmit powe, tansmit ate and diectional antenna contol The idea of TPC is to apply the lowest necessay tansmit powe that can maintain the communication between the sende and the eceive while consuming the least enegy [15 17]. Fo example, two contol packets, equest-to-send (RTS) and cleato-send (CTS), can be exploited to detect the link quality and thus to detemine the optimal powe level fo tansmitting data packets. Data tansmission uses the minimum necessay tansmit powe. Theefoe, it saves powe as well as educes spatial footpint. Howeve, RTS and CTS packets use the maximum powe fo ensuing the coect opeation of collision avoidance mechanism and thus, they ae unable to enhance the spatial utilization [17]. On the contay, smallest common powe (COMPOW) [18] and powe-stepped potocol (PSP) [17] use the same adio powe fo both data and contol packets but adaptively changes it depending on node and/o taffic density. A disadvantage of these TPC potocols is that they incu an additional ovehead to compute the optimal tansmit powe level, which may not be appopiate in dynamic, mobile envionment. On the othe hand, DAC is an explicit way of impoving spatial eusability because signal popagation and the coesponding intefeence ae limited to a cetain diection with diectional antennas [19 22]. Unfotunately, the well-know hidden teminal poblem [23] becomes even moe seious because moe neighbos ae ignoant o deaf to the ongoing communication. Altenatively, TRC exploits the physical laye multi-ate capability to make data tansfes moe obust to intefeence. Fo example, a eceive measues the channel quality based on the RTS it eceived and then infoms to the sende an appopiate data ate so that the channel can always be utilized at the highest feasible data ate. Accoding to Shannon, a cetain data ate is always achievable even if the SINR is not high. Moe concuent data tansfes can be enabled leading to moe spatial euse. Shepad studied the theoetic bounds of the netwok thoughput, assuming that the tansmit ate is abitaily adjustable [24]. Pabhaka et al. poposed an enegy-efficient communication schedule that takes the TRC capability into account [25]. And Sadeghi et al. poposed an oppotunistic media access scheme that bette exploits the channel via TRC and channel quality infomation [26] Caie sense contol CSC has been consideed ecently in the liteatue based on the assumption that the CS theshold is tunable within the detect sensitivity of the hadwae [9]. A highe CS theshold encouages moe concuent tansmissions but at the cost of moe collisions. On the othe hand, a lowe CS theshold educes the collision pobability but it equies a lage spatial footpint and pevents simultaneous tansmissions fom occuing, potentially limiting the netwok thoughput. Obviously thee is a tadeoff between high spatial euse and inceased chances of collisions [9]. Fuemmele, et al. studied the collision pevention conditions in this context and concluded that the poduct of tansmit powe and CS theshold should be kept to a fixed constant [1]. Yang and Vaidya [11] and Zhai and Fang [12] consideed the CSC adaptation while taking the influence of MAC ovehead and tansmit ate into consideation. These studies focused on analytic models fo obtaining aggegate thoughput. In compaison, ou focus in this pape is to develop a CSC algoithm that ealizes the optimal adaptation. Zhu, et al. used an analytical model to detemine the optimal CS theshold and

4 L. Song, C. Yu / Ad Hoc Netwoks 7 (29) poposed a distibuted algoithm, called adaptive physical caie sensing (APCS), that dynamically adjusts the CS theshold in mesh netwoks [13]. In APCS, ideally all the nodes use the same optimal CS theshold. The main eason behind the netwok-wide fixed CS theshold is fainess. Using the same CS theshold can give the nodes an equal chance to tansmit thei packets. This scheme was impoved ecently by adding eceive sensitivity adaptation [27]. The node s adio would not be locked onto the fist signal and thus becomes available to eceive any late-aiving signals [27]. It is consideed a eceive technique in the sense that a node is allowed not to eceive a signal even though it is stonge than the CS theshold. In contast, ou appoach in this pape is consideed a tansmitte technique because a node is allowed to tansmit its pending fame even in the pesence of caie signal. 3. System model CAD is an efficient MAC scheme that makes enough but no moe than necessay spatial and time esevation. Befoe explaining the CAD potocol in Section 4, this section descibes the system model assumed thoughout this pape and time-spatial spectal esouce eseved in DCF based on the model. Section 3.1 intoduces the signal popagation and eception model, which is used to estimate those esevation equiements. Section 3.2 explains DCF and its time-spatial egion eseved by the physical caie sensing (PCS) and vitual caie sensing (VCS) mechanisms. Section 3.3 discusses the optimal necessay esevation, which is then contasted with that of DCF A popagation and eception model Signal popagation in wieless channel is affected by path loss, shadowing and multiple-path fading. This pape assumes an open aea envionment whee path loss due to communication distance is the most impotant. Accoding to the coesponding two-ay gound eflection model [28], the eceive powe P (d) at distance d is given by ðh t h Þ 2 P ðdþ ¼P t G t G ð1þ d 4 L whee P t is the tansmit powe, G t and G ae the antenna gains of the tansmitte and the eceive, espectively, h t and h ae thei antenna heights, and L is the system loss. Table GHz Oinoco 11b Client PC Cad Specification (Nominal output powe of 15 dbm) [29]. Tansmit ate 1 Mbps 2 Mbps 5.5 Mbps 11 Mbps Receive 94 dbm 91 dbm 87 dbm 82 dbm sensitivity Range (open aea) 55 m 4 m 27 m 16 m To successfully eceive a tansmission the following two conditions have to be satisfied. Fist, the eceive must be within the tansmission ange of the sende. In othe wods, the eceive powe must be equal o lage than the eceive sensitivity. Given a adio hadwae and the tansmit powe level, the eceive sensitivity is mostly affected by tansmit ate. Table 1 shows thei elationship of the 2.4 GHz Oinoco 11b Client PC Cad [29]. Second, the eceive powe must be stong enough to ovecome the influence of the noise and intefeence. This condition is descibed by the following SINR model. SINR ¼ P N þ RI P Z ð2þ whee N is the backgound noise, RI is the intefeence fom all othe simultaneous tansmissions, and Z is the minimum equied SINR atio, commonly called captue atio. The SINR model tanslates that even if moe than one signal ovelaps at the eceive, one of them could suvive if it is much stonge than the sum of the othes. This is called the captue effect [14] and it suggests that a caeful coodination could make multiple communications be simultaneously successful even though they intefee with each othe. The CAD potocol poposed in this pape is such a coodination algoithm whee nodes do not have to eseve a lage space dictated by the CS theshold Time and spatial esevation in DCF Distibuted coodination function (DCF) is a MAC laye potocol defined in IEEE standad [1] and is used as a baseline MAC thoughout this pape. DCF adopts both PCS and VCS mechanisms to effectively avoid collisions. The PCS is implemented based on the clea channel assessment (CCA) function, which is one of sevice pimitives suppoted by IEEE PHY as shown in Table 2. Moe specifically, PHY CCA.indicate infoms by the PHY to the MAC that the medium is sensed busy and the MAC believes so until it is infomed

5 234 L. Song, C. Yu / Ad Hoc Netwoks 7 (29) Table 2 Sevice pimitives of IEEE [1]. Pimitives Request Indicate Confim PHY-DATA x x x PHY-TXSTART x x PHY-TXEND x x PHY-CCARESET x x PHY CCA x PHY-RXSTART x PHY-RXEND x othewise. Even afte PHY CCA.indicate infoms that the medium is fee, a node defes a little longe (extended intefame space o EIFS peiod of time). This is to potect the eception of an ACK fame. As fo spatial esevation in PCS, nodes in the poximity of the tansmitte would sense the caie signal and defe. The coesponding ange is called caie sense ange (CR) in this pape. On the othe hand, VCS is achieved by using RTS and CTS contol fames. Upon oveheaing an RTS o a CTS, a node consides the medium busy and holds its communication duing the time peiod specified in the Duation/ID field of the contol fames. The coesponding ange fom the tansmitte is called tansmission ange (TR). In summay, time esevation in DCF is based on the Duation/ID field in a MAC heade and the EIFS mechanism. Fo the fome, any neighbo who eceives o oveheas the MPDU would hono the esevation by withholding its data tansmission fo the specified amount of time. The latte is implemented by using the CCA function mentioned above. On the othe hand, the spatial esevation is not explicitly specified in DCF and is simply mandated fo those who eceive the fame. Fo example, conside that a fame is tansmitted. Node A eceives the fame successfully and it would defe based on the Duation/ID field in the fame. Node B, howeve, senses the fame but does not successfully eceive it (checksum eo). Node C does not even sense the fame. We can say that the spatial aea aound node A and node B has been eseved based on the VCS and PCS, espectively. But, the spatial esevation does not cove the aea aound node C. Fig. 1 shows the time-spatial esevation using PCS and VCS fo the communication between a sende (s) and a eceive (). Assuming that adio popagation is mostly affected by path loss, TR and CR tanslate to cicula egions aound the tansmitte as shown in the figue. And they denote spatial esevations based on VCS and PCS, espectively. Dotted ectangles denote the time-spatial esevation due to PCS and solid ectangles denote that due to VCS. As shown in the figue, this esevation changes ove time. Fig. 1a depicts the case of sende eceive distance of 2 m and Fig. 1b depicts the case of 1 m. TR and CR ae assumed to be 25 m and 55 m, espectively. Fom the figue, we made the following impotant obsevations. CR s TR s TR CR CR s TR s TR CR s RTS CTS s RTS CTS time Data Data ACK ACK space (a) Communication distance = 2m (b) Communication distance = 1m Receive egion Time-spatial esevation based on PCS & EIFS Caie sense egion Time-spatial esevation based on VCS (RTS/CTS) Fig. 1. Time-spatial esevation using PCS and VCS in DCF.

6 L. Song, C. Yu / Ad Hoc Netwoks 7 (29) Spatial esevation duing the DATA tansmission, which is usually the longest among the 4- way handshaking pocess, can be denotes as ðcr s [ CR Þ. A shote communication (Fig. 1b) eseves the simila time-spatial aea as a longe communication (Fig. 1a) in DCF, which in fact is a souce of inefficiency. While the PCS stats to be effective as soon as node s begins tansmitting a fame, the VCS becomes effective since afte the complete eception of the fame. This is because the Duation/ ID field is embedded in the MAC heade and can be used only afte it is confimed using the CRC checksum at the end of the MAC fame. This is anothe souce of inefficiency in DCF as will be explained in moe detail in the next section C intefeence ange and optimal time and spatial esevation We have seen the time-spatial esevation of the DCF in the pevious subsection. It is a consevative esevation but is consideed optimal in wieless LAN envionment because no concuent communication is suppoted. In multihop envionment, this consevative appoach diminishes the spatial eusability of the channel and it is equied to eseve the smallest necessay aea duing the smallest necessay time peiod. This subsection discusses the optimal (minimum) esevation equiements based on the adio popagation model descibed in Section 3.1. Fo this pupose, we intoduce intefeence ange (IR) which is the minimum sepaating distance between the eceive and a potential intefeing node such that the node does not cause collisions at the eceive. Unlike the fixed CR in DCF, IR vaies depending on communication distance (d) between the sende and the eceive, captue atio (Z ), as well as the numbe of intefees (k) and thei locations. It is noted that the optimal esevation equiement is IR because nodes outside of IR does not cause collisions. In the below, we fist of all (i) deive the IR with diffeent numbe of intefees (1 6 k 6 6, Fig. 2 and Eq. (3)), (ii) show that IR does not vay much with k as long as each case epesents the wost-case fo the given k (Fig. 3), (iii) solve fo the IR fo the case of k = 1 fo simplicity, and (iv) show it on Fig. 1 to eveal the ove-eseved time-spatial aea in DCF (Fig. 4). D 1 D 1 D 1 D 2 D 2 D 3 d D d D d D D 2 D 1 D 3 D 2 D 1 D 3 D 2 D 1 D 3 d D d D d D D 4 D 4 D D 5 4 D 5 D 6 pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi Fig. 2. Wost-case intefeence scenaios with k (1 6) fist-tie intefees D 1 ¼ D d, D 2 ¼ D 3 ¼ D 2 þ d 2 Dd, D 4 ¼ D 5 ¼ pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi D 2 þ d 2 þ Dd, D 6 ¼ D þ d.

7 236 L. Song, C. Yu / Ad Hoc Netwoks 7 (29) Dmin (m) Let D be the sepaating distance between the sende and an intefee. The optimal spatial esevation (IR) can be deduced using Eq. (2) intoduced in Section 3.1, i.e., SINR ¼ k=1 k=2 k=3 k=4 k=5 k=6 Communication distance, d (m) Fig. 3. D min 176 vesus d with vaying numbe of intefees (k). P ðdþ N þ P k i¼1 P ðd i Þ P Z ð3þ whee D i is the distance between the eceive and intefee i. Hee, only the fist-tie intefees (1 6 k 6 6) ae consideed [3] as in Fig. 2 because thei influence is dominant compaed to that of the second- and thid-tie intefees. To obtain the consevative estimate of the optimal spatial esevation o D min, each figue in Fig. 2 depicts the wost-case scenaio fo the given k, whee the intefees ae located to cause the maximum intefeence to the eceive. Now, given d, k, Z and N, it is not difficult to find D min that satisfies the inequality (3). Fig. 3 plots D min vesus the communication distance (d) with diffeing numbe of intefees (k) assuming that N is ignoable. To ou supise, it is obvious fom Fig. 3 that d almost dominates the influence. Fo example, when d is 15 m, the vaiation of D min with diffeent k is at most 7%. This is because the signal attenuates vey quickly with distance and thus the topmost intefee in each of the six figues in Fig. 2 (with the shotest distance to the eceive) dominates the intefeence. Due to this fact, each node in CAD estimates the spatial esevation based on the assumption that k = 1 and the intefee is located in the diection of the eceive as in the fist figue of Fig. 2. And, IR o D min ¼ 4p ffiffiffiffiffi Z d based on Eqs. (1) and (3). Consideing the fou-way handshaking pocess, the optimal spatial esevation to potect a communication is (IR s [ IR ). This must be contasted to the spatial esevation in DCF, (CR s [ CR ), as explained in Section 3.2. The optimal time-spatial esevation fo the communication between a sende (s) and a eceive () is shown in Fig. 4 assuming that Z = 1 db. In CR s IR s IR CR CR s CR TR s TR IR s TR s TR IR s RTS CTS s RTS CTS time Data Data ACK ACK space (a) Communication distance = 2m (b) Communication distance = 1m Receive egion Caie sense egion Ove-eseved Fig. 4. IR and ove-esevation in DCF.

8 L. Song, C. Yu / Ad Hoc Netwoks 7 (29) the figue, IR s and IR denote the optimal necessay spatial aea when node s o eceives, espectively. In the bottom of the figue, solid ectangles show unnecessay time-spatial aea that is eseved by the PCS and VCS in DCF. Ove-esevation is moe seious when the communication distance is shot as evident in Fig. 4b. The next section poposes CAD, whee each node adjusts its CS theshold based on the esevation equiement which in tun based on distance infomation of the ongoing as well as its own communication to potect both. 4. Collision-Awae DCF This section poposes a new MAC mechanism, called Collision-Awae DCF (CAD), which expenses the minimum time-spatial spectal esouce that is equied to successfully delive fames. Section 4.1 explains how it is facilitated in CAD. Section 4.2 explains how it is implemented in the context of standads. Section 4.3 intoduces how to estimate the spatial and time esevations. Section 4.4 discusses how to make tansmission decisions in the pesence of ongoing communication and thus incease the communication concuency Thee design consideations in CAD A basic idea of any caie sensing MAC is to defe a node s communication when the node senses an ongoing communication. It avoids collisions and thus impoves the oveall netwok pefomance. Fom a communicating pai s point of view, they make a time and spatial esevation to potect thei communication. A question is how to accuately estimate the esevation equiements and how to let thei neighbos know the esevation. In DCF, time esevation is specified in the Duation/ID field in the MAC heade of a MAC potocol data unit (MPDU) fame as descibed in Section 3.2. Spatial esevation in DCF is implicit but is fa fom optimal, paticulaly in multihop MANET envionment. The main goal of the poposed CAD potocol is to make an optimal time and spatial esevation to maximize the pefomance of multihop netwoks. Thee key consideations in this egad ae: (i) Explicit spatial esevation, (ii) esevation infomation in PHY athe than MAC fame (MPDU) heade, and (iii) time-spatial esevation limited to the vey next fame instead of the end of the fame exchange sequence (RTS, CTS, DATA and ACK). Note that these thee consideations ae specifically tageted at multihop netwoks. In wieless LANs, these issues ae not citically impotant and thus lagely ignoed in the cuent design of standads. Explicit spatial esevation: In MANETs, a pudent spatial esevation as well as time esevation should be consideed because it maximizes the channel utilization by allowing moe concuent communications [31]. Resevation infomation in PHY athe than MAC fame heade: In DCF, the esevation infomation is embedded in the MAC fame heade and is popagated to the tansmitte s neighbohood. Nodes outside of the tansmitte s tansmission ange would be ignoant of the esevation. Without knowing the esevation equiement, the easiest way to avoid collisions is to defe one s tansmission wheneve doubtful. The EIFS mechanism, explained in Section 3.2, implements this in DCF. CAD eliminates the unnecessay defement by popagating the esevation infomation to a wide goup of neighbos by embedding the esevation infomation in the PHY heade. Note that while the MAC heade can be tansmitted at a highe ate, the PHY heade (o called PLCP heade) is always tansmitted at the lowest data ate o 1 Mbps in o 82.11b standads and thus tavels a fathe ange. Time-spatial esevation limited to the vey next fame instead of the end of the fame exchange sequence: In DCF, a tansmitte estimates the time fo the completion of the fame exchange sequence (i.e., RTS, CTS, DATA and ACK), which constitutes the Duation/ID field of a MAC heade. It is used to set netwok allocation vecto (NAV) of the nodes in the tansmitte s neighbohood to make time esevation. In CAD, the spectal esouce is eseved only fo the cuent and the following fame. It is beneficial because of the followings. Fist, conside a communication that is poceeded by RTS and CTS contol fames. When RTS CTS exchange fails, neighbos would still defe duing the estimated completion time of the communication assuming that the fou-way handshaking is successful. In CAD, neighbos would defe until the estimated eception time of the next fame (CTS) eliminating the unnecessay defement o spectal esouce wastage. Second, in DCF, thee

9 238 L. Song, C. Yu / Ad Hoc Netwoks 7 (29) exists a potential fainess poblem. Conside the same example as above whee the RTS CTS exchange fails. The failed tansmitte will obtain anothe chance to etansmit an RTS immediately (afte waiting a DIFS) because othe nodes would defe thei tansmissions fo a longe time. In CAD, neighbos do not defe fo the peiod of an entie fame exchange sequence and theefoe, the fainess poblem is avoided. Thid, as the fou-way handshaking pogesses, the tansmitte and the eceive will have a moe accuate estimate on the equied spatial esouce based on the feedback fom the countepat of the communication. In CAD, spatial esevation in RTS fame is made in a consevative way as in DCF. Howeve, spatial esevation in CTS and DATA fame will be estimated smalle than in DCF leading to a highe utilization of the spectal esouce PLCP fame fomat and handling esevation equiements Fig. 5 shows the PLCP fame fomat in CAD, whee spatial and time esevation equiements ae embedded. They ae efeed to as REQ_SR and REQ_TR, espectively. As discussed in the pevious subsection, the benefit of embedding the esevation infomation in the PLCP heade is that it is popagated to a wide goup of neighbos because the PLCP heade is tansmitted at the lowest data ate (1 Mbps in and 82.11b). Data ate used fo the PHY payload (MPDU) tansmission is indicated by the 8-bit SIGNAL field of the PLCP heade in Fig. 5. Anothe benefit is based on the fact that the esevation infomation in the MAC heade cannot be utilized while the MPDU is being eceived. This is because an MPDU fame is not consideed legitimate until the whole packet is eceived and its CRC checksum is confimed. When a node oveheas a long DATA fame, it will be beneficial to know whethe it can safely tansmit its own fame even befoe the complete eception of the cuent fame. This is in fact accomplished in CAD by including the time and spatial esevation infomation in the PLCP heade. The PLCP heade is eceived and confimed fo its integity even befoe a node stats eceiving the PHY payload (MPDU fame). This small change makes the CAD algoithm much simple because it is possible in CAD fo each node to be esponsible fo the cuent fame as well as the subsequent fames. It is moe effective when RTS/CTS contol fames ae not used. On the othe hand, CAD is disadvantageous as it inceases the fame size. When the communication channel is bad and is chaacteized by a high bit eo ate (BER), each tansmission in CAD could be moe subjective to couption than in DCF. Howeve, the fame size incease is not lage enough to make a significant impact on netwok pefomance. Fo example, fo a 512-byte PHY payload (MPDU), the PHY fame size inceases fom 4288 to 432 bits, which is just a.7% incease. Fame tansmit and eceive pocedues in CAD ae vey simila to those in standads with little changes. When a tansmitte s MAC equests a fame tansmission to its PHY, a set of paametes ae summaized in TXVECTOR and passed to its PHY laye along with PHY_TXSTART.equest [1] Indicating tansmit ate fo MPDU Resevation equiements SYNC 128 bits SFD 16 bits SIGNAL 8 bits SERVICE 8 bits LENGTH 16 bits REQ_SR 16 bits REQ_TR 16 bits CRC 16 bits PLCP Peamble 144 bits PLCP Heade 8 bits MPDU Always 1Mbps Data ate specified in SIGNAL field Fig. 5. PLCP fame fomat whee REQ_SR and REQ_TR ae added. (This fame fomat is based on and 82.11b Long Peamble PLCP fame fomat. In 82.11b Shot Peamble PLCP fame fomat, SYNC filed is 64 bits.)

10 L. Song, C. Yu / Ad Hoc Netwoks 7 (29) MAC PHY_TXSTART.equest (TXVECTOR) PHY_DATA.equest (DATA) PHY SYNC, SFD SIGNAL, SERVICE, LENGTH REQ_SR, REQ_TR CRC MPDU CRC stat CRC end Rate change stat (a) Tansmit pocedue (TXVECTOR includes REQ_SR and REQ_TR) If (RSSI < REQ_SR and RSSI < REQ_SR ) medium is consideed idle (see Section IV.D) MAC PHY_CCA.indicate (BUSY) PHY_RXSTART.indicate (RXVECTOR) PHY SYNC, SFD SIGNAL, SERVICE, LENGTH REQ_SR, REQ_TR CRC MPDU CRC stat CRC end Rate change stat (b) Receive pocedue (RXVECTOR includes REQ_SR and REQ_TR) Fig. 6. Tansmit and eceive pocedues in CAD. as shown in Fig. 6a. Note that the data ate used fo MPDU tansmission is indicated in the 8-bit SIG- NAL field as discussed ealie. Fig. 6b shows the PLCP eceive pocedue. Upon detecting a coming signal, PHY_CCA.indicate (BUSY) will be issued to the MAC laye if the signal stength is highe than CS theshold. Then the PHY laye will begin seaching fo stat fame delimite (SFD) and stat to eceive a PLCP heade. If a PLCP heade is successfully eceived (CRC check passes), the PHY_RX- START (RXVECTOR) will be issued to the MAC laye accoding to the The RXVECTOR contains the infomation of SIGNAL field, SER- VICE field, LENGTH field, RSSI, signal quality, and antenna used fo eceive. In CAD, a tansmitte estimates the esevation equiements, REQ_SR and REQ_TR, fo potecting its communication and adds this infomation in the TXVECTOR as shown in Fig. 6a. The tansmitte s neighbos as well as the designated eceive obtain the esevation equiements and decide whethe o not to defe. Similaly, in Fig. 6b, when a node eceives a fame, it obtains infomation included in the PLCP heade including the esevation equiements. They will be passed to the MAC in the fom of RXVECTOR, which includes REQ_SR and REQ_TR Estimating spatial and time esevation equiements A main question in CAD is to accuately estimate the esevation equiements at a tansmitte. Estimation of REQ_TR is based on fame length, fame type and data ate. Unlike 82.11, it is until the completion of the cuent and the next fame in the fou-way handshaking pocess. Fo example, time esevation fo a CTS fame is estimated as (SIFS + DATA + SIFS + ACK) and (CTS + SIFS + DATA) in DCF and CAD, espectively. Hee, CTS, DATA and ACK denote the time tansmit the coesponding fames. SIFS stands fo shot intefame space. Note that CTS is not included in the time esevation of DCF, which was explained in Section 4.2. Regading the spatial esevation equiements, we fist of all compae that of DCF and CAD fo two node pais with communication distance of 1 m and 2 m as in Fig. 7. Fo bevity, the figue shows the spatial esevation duing the DATA tansmission only. It is clea fom the figue that DCF eseves a much lage spatial aea than CAD, which is moe pominent when the communication distance is shote as in Fig. 7b and d. Fo example, in Fig. 7d, when d = 1 m, the tansmitte s (node s) signal aiving at the eceive (node

11 24 L. Song, C. Yu / Ad Hoc Netwoks 7 (29) CR s IR s IR CR CR s CR TR s TR IR s TR s TR IR s s (a) DCF (d=2m) (b) DCF (d=1m) CR s IR s IR CR CR s CR TR s TR IR s TR s TR IR s s (c) CAD (d=2m) (d) CAD (d=1m) Fig. 7. Spatial esevation (shaded aea) duing the DATA tansmission. (CR s [ CR in DCF and IR s [ IR in CAD. DCF eseves a much lage aea than CAD leading to spectal esouce wastage.) ) is much stonge than necessay and thus is esilient to intefeence. This means that its neighbos could tansmit thei own fames without disupting the s communication. In othe wods, nodes outside of the shaded aea (eseved aea) in Fig. 7dcan concuently tansmit in CAD allowing a highe channel utilization than in DCF shown in Fig. 7b. As discussed in Section 3.3, REQ_SR o the optimal spatial esevation is D min ¼ 4p ffiffiffiffiffi Z d. This is the maximum intefeence level that the eceive can toleate. A key issue is how to tanslate any measuable quantity such as signal stength infomation (e.g., eceived signal stength indicato o RSSI) to communication distance assuming Z is known. We assume in this pape that RSSI can be tanslated to distance infomation. Even though it does not hold, the basic idea of CAD can still be applicable because RSSI itself can be used as the spatial esevation equiement. Fo example, when a tansmitte eceives a CTS, it can measue the RSSI while eceiving the fame. The highe the RSSI, they can toleate a highe intefeence and thus thei spatial esevation equiement is smalle. Moe specifically, when a node (say, node ) tansmits a fame, it includes the spatial esevation equiement (REQ_SR) in its PHY fame heade. It essentially says any node within REQ_SR should defe. In othe wods, any node that is sepaated by d fom node and 6 d should defe. On the othe hand, let us assume that the distance infomation is not available but RSSI is available fo use in place of REQ_SR. The spatial esevation equiement in the PHY heade says any node that eceives the signal with the signal stength of RSSI and 1/ RSSI 6 1/REQ_SR should defe Setting NAV and making tansmission decisions In DCF, a node decides to tansmit its fame only when no caie is sensed (PCS) and NAV is zeo (VCS). Fo the latte, NAV is set to the Duation/ID field in the MPDU upon eceiving a legitimate fame. Fo an eed fame, NAV is set to EIFS upon the end of the fame as explained in Section 3.2. Both mechanisms ae to potect the ongoing communication. Since CAD attempts to eseve the minimum necessay time and spatial esouce, a cae must be taken

12 L. Song, C. Yu / Ad Hoc Netwoks 7 (29) not to intefee the ongoing communication as well as not to be intefeed by the ongoing communication. Conside the case in Fig. 7d. A potential tansmitte (say, node A) outside of the shaded aea is fee to stat its communication, fo example, with node B. Although node A is sue that it does not cause any touble to the s communication, but it is not clea whethe A s communication is intefeed by the s communication o not. This is cleae in Fig. 8. Node A s tansmission would not intefee node s communication in Fig. 8a and b because node A is outside of node s spatial esevation equiement (REQ_SR). Howeve, node A does not always decides to tansmit its own fame because it may be intefeed by node s communication if it stats. It depends on node A s spatial esevation equiement (REQ_SR ). In Fig. 7a, node A needs a small REQ_SR and node is outside of the REQ_SR. Theefoe, node A decides to tansmit. On the othe hand, in Fig. 8b, node A demands a lage REQ_SR and node is inside the shaded aea. Node A, in this case, decides not to tansmit because its communication could be intefeed by node s communication. In summay, the tansmission decision is based on the answes fo the following two questions: (i) Whethe its communication is successful if it tansmits concuently with the ongoing data tansfe. (ii) And, whethe the ongoing communication is successful if it tansmits. Fo the fome question, the node compaes the RSSI of the incoming signal with its own spatial equiement (REQ_SR ). (Hee, we assume that RSSI and REQ_SR ae conveted to an equivalent measue, such as distance o signal stength.) In othe wods, the node defes if RSSI P REQ_SR because the stength of the incoming signal exceeds the maximum intefeence level that its outgoing tansmission can toleate. Fo the latte, the node compaes the RSSI of the incoming signal with REQ_SR of the ongoing tansmission i.e., the node defes if RSSI P REQ_SR because the ongoing communication would fail if the node tansmits. This is based on the assumption that the link is symmetic; The RSSI of the incoming signal is equal to the RSSI (intefeence) that the node would cause to the ongoing tansmission. As a esult, if RSSI P REQ_SR o RSSI P REQ_SR, the medium is consideed busy and the node defes its tansmission. In this case, the PHY will continue to eceive MPDU but NAV is set to a new REQ_TR obtained fom the incoming PLCP heade. On the othe hand, if RSSI < REQ_SR and RSSI < REQ_SR, the medium is consideed idle. In this case, the PHY will issue PHY_CCA.indicate (IDLE) to the MAC laye so that the node can tansmit its fame even though thee is an ongoing communication as shown in Fig. 6b in Section 3.2. Theefoe, CAD encouages moe concuent communications as long as they do not intefee with each othe and thus inceases the netwok thoughput. 5. Pefomance evaluation In ode to evaluate the pefomance impovement of CAD, this section compaes CAD with DCF based on ns-2 [32]. Section 5.1 explains the simulation envionment and Section 5.2 pesents simulation esults with discussions Simulation envionment Ou pefomance study is based on the simulation of 5 mobile nodes distibuted on a 3 15 m 2 aea. Radio popagation model used is two-ay A A REQ_SR REQ_SR REQ_SR REQ_SR (a) Node A decides to tansmit (b) Node A decides not to tansmit Fig. 8. Making a tansmission decision. (Node is cuently communicating and the coesponding spatial esevation equiement is REQ_SR. Node A is a potential tansmitte and it demands REQ_SR.)

13 242 L. Song, C. Yu / Ad Hoc Netwoks 7 (29) gound popagation model as discussed in Section 3.1 and Eq. (1). Tansmit ange (TR) of 25 m and caie sense ange (CR) of 55 m is assumed. Captue atio (Z ) of 1 db is used in ou pefomance study. Regading signal tansmission and captue, we have extended ns-2 as follows. In the oiginal implementation of the ns-2, the signal stength compaison is pe-packet based. That is, the eceive compaes the most-ecently-aiving packet only with the one it is eceiving. We modified thens-2 to allow each node to tack evey incoming signal so that the effect of the additive intefeence can be simulated. Since this pape assumes that adio hadwae uses diffeent data ates fo PLCP heade and MPDU, we modified ns-2 to suppot multi-ate communication. The PLCP heade is tansmitted at 1 Mbps while the MPDU is tansmitted at 2 Mbps. The movement of the nodes is descibed by the andom waypoint mobility model with the maximum speed of 5 m/s and with the pause time of 9 s. Ten to fifty CBR (constant bit ate) taffic is used to simulate the netwok taffic. Ad hoc on-demand distance vecto (AODV) outing potocol [33] is used in ou study to detemine the outing path between the souce and the destination. The simulation time is 9 s and each simulation scenaio is tested with five uns to obtain the aveage pefomance measues Simulation esults and discussion This subsection pesents simulation esults compaing the pefomance of the poposed CAD with DCF and APCS [13]. Packet delivey atio (PDR) and packet delay ae used as pimay pefomance metics as shown in Fig. 9. The pause time vaies between and 9 s. Note that pause time of 9 s tanslates to a static netwok whee nodes do not move because the simulation time is 9 s. On the othe hand, pause time of s coesponds to a constant moving scenaio. Thity CBR connections ae simulated whee souce and destination nodes ae chosen andomly among the 5 mobile nodes. Each taffic souce geneates thee 124-byte packets evey second. As clealy seen in Fig. 9a and b, CAD outpefoms DCF and APCS with a lage magin. It achieves 16 19% highe PDR and 59 76% lowe packet delay than DCF. Compaed to APCS, it achieves 11 13% highe PDR and 32 67% lowe delay. The damatic pefomance impovement of CAD ove DCF is attibuted to highe concuency and yet its excellent capability in avoiding collisions. While nodes make tansmission decisions depending on the caie signal and the pe-detemined CS theshold in DCF, the CAD potocol allows the nodes to make moe intelligent decisions based on infomation fom thei neighbos. The eason why APCS does not pefom well compaed to DCF is that it basically is a consevative scheme as well. In APCS, a node detemines its CS theshold by taking the minimum of it s neighbos CS thesholds. When a node steps down its CS theshold, it is possible that all its neighbos step down leading to a suboptimal spatial esevation. CAD poduces moe communication oppotunities but educes collisions as evident in Fig. 9c and d, espectively. Note that we investigated the numbe of RTS tansmissions and thei collisions fo this pupose because evey outing o data packet is peceded by a RTS packet. Fig. 9c shows the numbe of RTS packets tansmitted duing the simulation. With CAD, nodes send 6 2% moe RTS packets (communication oppotunities) than with DCF, which is 12% than APCS. Howeve, CAD esults in 7 11% less collisions on RTS packets as shown in Fig. 9d. Compaed to APCS, it is 9 14% less collisions. Note that Fig. 9c does not count the etansmitted RTS packets because moe etansmissions mean moe collisions athe than moe communication oppotunities. On the othe hand, Fig. 9d includes both initial and etansmitted RTS packets because we wanted to know the oveall collision pobability. In ode to undestand how CAD impoves the pefomance, we measued MAC laye contol ovehead as well as the packet queue size as shown in Table 3 and Fig. 1. One impotant advantage of CAD is shot packet delay as in Fig. 9b. Ou investigation shows that packet queuing delay is an impotant ingedient fo this. Having moe communication oppotunities in CAD facilitates a mobile node to quickly offload pending packets and theefoe, it helps keep its packet queue at each node as shot as possible. In each of 9 s of simulation uns, we collected packet queue size evey 1 s at each node and calculated the aveage statistics acoss all mobile nodes in the netwok. As shown in Table 3, each node has about and packets in its queue on the aveage with DCF and APCS, espectively, while it is.17.87

14 L. Song, C. Yu / Ad Hoc Netwoks 7 (29) DCF APCS CAD.6.3 DCF APCS CAD Pause time(seconds) (a) Packet delivey atio (%) Pause time (seconds) (b) Packet delay (seconds) Pause time (seconds) DCF APCS CAD (c) Numbe of RTS packets (pe second) DCF APCS CAD Pause time (seconds) (d) RTS collision atio (%) Fig. 9. Pefomance compaison with mobility. Table 3 Aveage packet queue size Pause time (seconds) DCF APCS CAD with CAD. This amounts as much as 9% and 8% eduction in packet queue size in compaison to DCF and APCS, espectively. To obseve the MAC contol ovehead, we measue the MAC laye contol taffic (RTS, CTS and ACK) in DCF, APCS and CAD as in Fig. 1a. Although they geneate about the same amount of MAC laye ovehead, its detailed figues ae quite diffeent. Fo example, the numbe of RTS packets is almost the same in DCF, APCS and CAD but this is only tue fo the combined initial and etansmitted RTS packets. While CAD allows moe numbe of initial RTS packets as aleady seen in Fig. 9c, it causes less RTS etansmissions than DCF and APCS. Similaly, the total numbe of ACK packets is simila among the thee potocols. Howeve, CAD esults in moe ACKs than DCF and APCS in esponse to DATA packets while it is exactly the opposite fo ACKs in esponse to RREP packets as shown in Fig. 1b indicating that CAD uses moe bandwidth fo useful data tansmission than DCF and APCS. One impotant advantage of CAD is shot packet delay as shown in Fig. 9b. Ou investigation shows

15 244 L. Song, C. Yu / Ad Hoc Netwoks 7 (29) ACK (DATA) ACK (RREP) ACK CTS RTS DCF APCS CAD Pause time(seconds) (a) MAC contol ovehead DCF APCS CAD Pause time (seconds) 6 9 (b) A detailed analysis of ACK packets DCF APCS CAD DCF APCS CAD Pause time (seconds) (c) Aveage packet queue size Pause time (seconds) (d) Fainess index Fig. 1. Othe pefomance measues including MAC ovehead. that packet queuing delay is an impotant ingedient fo this. Having moe communication oppotunities in CAD facilitates a mobile node to quickly offload pending packets and theefoe, it helps keep its packet queue at each node as shot as possible. In each of 9 s of simulation uns, we collected the packet queue size evey 1 s at each node and calculated the aveage statistics acoss all mobile nodes in the netwok. As shown in Fig. 1c, each node has about and.9 1. packets in its queue on the aveage with DCF and APCS, espectively, while it is.2.9 with CAD. Anothe impotant measue in evaluating the CAD potocol is fainess. Since nodes may not defe thei tansmissions even though they sense the medium busy, it might cause unfainess among communication links. In ode to compae the fainess of the MAC algoithms, we measued fainess index, defined as follows [34,35]: P N i¼1 c 2 i F ¼ N P N i¼1 c2 i ð4þ whee N is the numbe of connections and c i is the numbe of eceived packets fo connection i. The value of this index anges fom (completely unfai) to 1 (pefectly fai). Accoding to ou simulation esult shown in Fig. 1d, CAD does not hut the fainess of communications. On the contay, it impoves it in compaison to DCF and APCS. We think that offloading of packets soone than othe potocols helps impove the fainess in CAD. Fig. 11a and b depict the effect of taffic intensity in tems of the numbe of connections of CBR

16 L. Song, C. Yu / Ad Hoc Netwoks 7 (29) PDR (%) 6 4 PDR (%) DCF APCS CAD Numbe of connections 2 DCF APCS CAD Numbe of nodes (a) Effect of the numbe of connections (b) Effect of the numbe of nodes Fig. 11. Scalability analysis. taffic and node density. The numbe of connections vaies fom 1 to 5 in Fig. 11a, and the numbe of nodes changes fom 75 to 175 in Fig. 11b. In both scenaios, the same data ate and packet size (thee 124-byte packets pe second) ae used. As shown in the figue, CAD consistently outpefoms DCF and APCS although both of them suffe when the numbe of connections inceases in Fig. 11a. Recent expeimental studies show that shotest (hop count) path does not always povide the best pefomance because it usually consists of longe hops, each of which is easily subjective to intefeence with a small SINR [4,36]. In ode to see how CAD pefoms in a moe ealistic envionment, a set of expeiments has been conducted with the shadowing popagation model instead of the conventional two-ay gound popagation model intoduced in Section 3.1. Shadowing is caused by the lack of visibility between two communicating nodes and it causes slow vaiations ove the mean eceived powe. The mean eceived powe is calculated deteministically based on the communication distance. The andomness of channel is descibed by a lognomal andom vaiable, the distibution function of which is Gaussian with zeo mean and a specified standad deviation (SD). Befoe pesenting the simulation esults, Fig. 12a shows how the adio channel behaves with the 1 Success atio (%) SD=.dB SD=4.dB SD=6.dB SD=8.dB SD=1. db Distance (m) (a) Success atio with distance PDR (%) DCF APCS CAD SD (b) Packet delivey atio (%) Fig. 12. Effect of andom channel.

17 246 L. Song, C. Yu / Ad Hoc Netwoks 7 (29) shadowing model pesenting the success atio vesus communication distance using ns-2. In case of SD of. db, the shadowing model is equivalent to the deteministic two-ay gound model and thus the success atio is 1% if the distance is less than 25 m, which is the tansmission ange. Othewise, it is %. As SD inceases, moe communications fail even if the distance is less than 25 m, and moe communications succeed even if the distance is longe than 25 m. When the communication distance is 2 m, the success atio is 42% with SD of 1 db. Less than a half of the tansmission attempts can be successful even if the communication distance is shote than the tansmission ange. Fig. 12b shows the effect of channel andomness in tem of SD on the netwok pefomance. CAD consistently pefoms bette than DCF and APCS in tems of PDR. Howeve, the PDR magin between CAD and the othe two decease when SD is getting lage. This is because in CAD the REQ_SR calculation is deteministic and based on the communication distance only. It means that the REQ_SR estimation is not accuate in andom channel. The moe andom the channel is, the moe eo the estimation contains. Coespondingly, the pefomance magin educes. Efficient opeation in the pesence of andomness of the communication channel compises one of ou futue woks. 6. Conclusions and futue wok This pape poposes Collision-Awae DCF (CAD) mechanism that encouages moe concuent tansmissions but at the same time avoids collisions moe efficiently. While the DCF avoids collisions based on a pe-detemined caie sense theshold (physical caie sense o PCS) and advetise of the communication duation embedded in the MAC heade (vitual caie sense o VCS), both methods often fail to achieve the maximum achievable pefomance, paticulaly in multihop netwok envionment. In CAD, each node estimates the ange that it wishes to eseve fo its data tansfe (spatial esevation equiement) and the time duation (time esevation equiement) based on the communication distance o eceived signal stength. And, they ae embedded in the PHY heade of the tansmitted packet so that a lage goup of potential intefees become awae of it and ahead of time. Ou simulation study based on ns-2 shows that CAD significantly impoves the netwok pefomance in tems of packet delivey atio and packet delay. It is obseved that the benefit of CAD comes fom moe numbe of concuent tansmissions and smalle collision atio, which in fact was the oiginal goal of the CAD mechanism. CAD is designed to be compatible with TPC and TRC capability in the sense that estimation of the spatial esevation equiement can easily accommodate the tansmit powe and tansmit ate infomation. This issue needs futhe study and is emained as a futue wok. Refeences [1] IEEE Std , Local and metopolitan aea netwok, specific equiements, Pat 11: Wieless LAN medium access contol (MAC) and physical laye (PHY) Specifications, < pdf>. [2] A. Uma, Wieless LANs and mobile ad hoc netwoks, mobile computing and wieless communications, NGE Solutions Inc. (24) (Chapte 6). [3] I.F. Akyildiz, X. Wang, W. Wang, Wieless mesh netwoks: a suvey, Comput. Netwoks J. (Elsevie) (25). [4] J. Bicket, D. Aguayo, S. Biswas, R. Mois, Achitectue and evaluation of an unplanned 82.11b mesh netwok, IEEE/ ACM Mobicom (25). [5] W. Ye, J. Heidemann, D. Estin, An enegy-efficient mac potocol fo wieless senso netwoks, IEEE INFOCOM (22) [6] J. Hill, R. Szewczyk, A. Woo, S. Holla, D. Culle, K. Piste, System achitectue diections fo netwok sensos, ASPLOS (2). [7] R. Ramanathan, A adically new achitectue fo next geneation mobile ad hoc netwoks, ACM Mobicom (25). [8] A. Kameman, L. Monteban, WaveLAN-II: a high-pefomance wieless lan fo the unlicensed band, Bell Labs Tech. J. Summe (1997) [9] F. Ye, S. Yi, B. Sikda, Impoving spatial euse of I EEE based ad hoc netwoks, IEEE GLOBECOM (23). [1] J. Fuemmele, N. Vaidya, V. Veeavalli, Selecting tansmit powes and caie sense thesholds fo CSMA potocols, Technique epot, Univesity of Illinois at Ubana-Champaign, Octobe 24. [11] X. Yang, N. Vaidya, On the physical caie sense in wieless ad hoc netwoks, IEEE INFOCOM (25). [12] H. Zhai, Y. Fang, Physical caie sensing and spatial euse in Multiate and Multihop wieless ad hoc netwoks, IEEE INFOCOM (26). [13] J. Zhu, X. Guo, L.L. Yang, W.S. Conne, S. Roy, M.M. Haza, Adapting physical caie sensing to maximize spatial euse in mesh netwoks, Wieless Commun. Mobile Comput. (4) (24) [14] M. Zozi, R. Rao, Captue and etansmission contol in mobile adio, IEEE J. Selected Aeas Commun. 12 (8) (1994) [15] J.P. Monks, V. Bhaaghavan, W.W. Hwu, A powe contolled multiple access potocol fo wieless packet netwoks, IEEE INFOCOM (21). [16] J. Monks, J.-P. Ebet, W.-M.W. Hwu, A. Wolisz, Enegy saving and capacity impovement potential of powe contol

18 L. Song, C. Yu / Ad Hoc Netwoks 7 (29) in multi-hop wieless netwoks, Comput. Netwoks 41 (23) [17] C. Yu, K.G. Shin, B. Lee, Powe-stepped potocol: enhancing spatial utilization in a clusteed mobile ad hoc netwok, IEEE J. Selected Aeas Commun. 22 (7) (24) [18] S. Naayanaswamy, V. Kawadia, R.S. Seenivas, P.R. Kuma, Powe contol in ad hoc netwoks: theoy, achitectue, algoithm and implementation of the COMPOW potocol, Eu. Wieless Conf. (22) [19] Y.B. Ko, V. Shankakuma, N.H. Vaidya, Medium access contol potocols using diectional antennas in ad hoc netwoks, IEEE INFOCOM (2). [2] M. Takai, J. Matin, R. Bagodia, A. Ren, Diectional vitual caie sensing fo diectional antennas in mobile ad hoc netwoks, ACM MobiHOC (22). [21] Y. Wang, J.J. Gacia-Luna-Aceves, Spatial euse and collision avoidance in ad hoc netwoks with diectional antennas, IEEE GLOBECOM (22). [22] T. Koakis, G. Jakllai, L. Tassiulas, A MAC potocol fo full exploitation of diectional antennas in ad hoc wieless netwoks, ACM MobiHOC (23). [23] J. Schille, Wieless LAN, Mobile Communications, Addison-Wesley, Halow, UK, 2. [24] T.J. Shepad, A channel access scheme fo lage dense packet adio netwoks, ACM SIGCOMM (1996). [25] B. Pabhaka, E. Uysal-Biyikoglu, A. El Gamal, Enegyefficient tansmission ove a wieless link via lazy packet scheduling, IEEE INFOCOM (21) [26] B. Sadeghi, V. Kanodia, A. Sabhawal, E. Knightly, OAR: An oppotunistic autoate media access potocol fo ad hoc netwoks, ACM MobiCom (22). [27] J. Zhu, B. Metzle, X. Guo, Y. Liu, Adaptive CSMA fo scalable netwok capacity in high-density WLAN: a hadwae pototyping appoach, IEEE INFOCOM (26). [28] T. Rappapot, Wieless communications: pinciples and pactice, second ed., Pentice Hall Communications Engineeing and Emeging Technologies Seies, Pentice Hall, 22. [29] Oinoco 11b Client PC cad specification. Available fom: < pdf,25>. [3] X. Yang, N. Vaidya, On the physical caie sense in wieless ad hoc netwoks, IEEE INFOCOM (25). [31] C. Yu, K.G. Shin, L. Song, Maximizing communication concuency via link-laye packet salvaging in mobile ad hoc netwoks, IEEE Tans. Mobile Comput. 6 (4) (27). [32] The Netwok Simulato ns-2, < ns/>. [33] C.E. Pekins, E. Roye, Ad hoc on-demand distance vecto outing, IEEE Wokshop on Mobile Computing Systems and Applications, 1999, 9 1. [34] R. Jain, The At of Compute Systems Pefomance Analysis, John Wiley and Sons, [35] T. Nadeem, L. Ji, A. Agawala, J. Age, Location enhancement to IEEE DCF, in: Poceedings of IEEE INFOCOM, Mach 24. [36] R. Daves, J. Padhye, B. Zill, Compaison of outing metics fo static multi-hop wieless netwoks, ACM SIGCOMM, 24. Lubo Song eceived the B.S. degee in Compute Science and M.S. in Electical Engineeing fom Chongqing Univesity, China in 1993 and 1996, espectively. He has been a candidate fo Docto of Engineeing at Cleveland State Univesity, Cleveland, Ohio since 22. His eseach inteests include wieless ad hoc and senso netwoks, mobile computing, and softwae engineeing. Chansu Yu eceived the B.S. and M.S. degees in electical engineeing fom Seoul National Univesity, Koea, in 1982 and 1984, espectively, and the Ph.D. degee in compute engineeing fom the Pennsylvania State Univesity in He is cuently an Associate Pofesso in the Depatment of Electical and Compute Engineeing at the Cleveland State Univesity in Cleveland, Ohio. Befoe joining the CSU, he was on the eseach staff at LG Electonics, Inc. fo nine yeas until 1997 and was on the faculty at Infomation and Communications Univesity, Koea duing He has been a co-chai fo IEEE PeCom wokshop on pevasive wieless netwoking fo thee consecutive yeas (PWN7, PWN6 and PWN5) and intenational wokshop on mobile and wieless ad hoc netwoking (MWAN5 and MWAN4). He also has been on the pogam committees of seveal intenational confeences including The 1st intenational wokshop on RFID and ubiquitous senso netwoks (USN 25), The 1st IEEE intenational confeence on mobile ad hoc and senso systems (MASS, 24), and 23 intenational confeence on paallel and distibuted computing systems (ICPDCS). He is also a guest edito of jounal of pevasive computing and communications (JPCC), special issue on Wieless Netwoks and Pevasive Computing in 25. His eseach inteests include mobile wieless netwoks, senso netwoks, paallel and clusteing computing, and pefomance modeling and evaluation. He has authoed/coauthoed moe than 6 technical papes and numeous book chaptes in the aeas of mobile netwoking, pefomance evaluation and paallel and distibuted computing. He is a membe of the ACM, IEEE and IEEE Compute Society.