Increasing Throughput and Reducing Delay in Wireless Sensor Networks Using Interference Alignment

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1 Int. J. Communication, Network and Sytem Science, 0, 5, Publihed Online February 0 ( Increaing Throughput and Reducing Delay in Wirele Senor Network Uing Interference Alignment Vahid Zibakalam, Mohammad Hoein Kahaei School of Electrical Engineering, Iran Univerity of Science and Technology, Tehran, Iran vahid.zibakalam@gmail.com, kahaei@iut.ac.ir Received December, 0; revied January 9, 0; accepted February, 0 ABSTRACT With the advent of enor node with higher communication and ening capabilitie, the challenge arie in forming a data gathering network to maximize the network capacity. The channel haring for higher data tranmiion lead to interfering problem. The effect of interference become increaingly important when imultaneou tranmiion are done in order to increae wirele network capacity. In uch cae, achieving a high throughput and low delay i difficult. We propoe a new method that ue interference alignment (IA) technique to mitigate interference effect in Wirele Senor Network (WSN). In IA technique, multiple tranmitter jointly encode their ignal to intended receiver uch that interfering ignal are eparated and eliminated. Simulation reult demontrate that compared to TDMA algorithm, the propoed method ignificantly increae the performance of the network delay and throughput by reducing the delay and increaing throughput. Keyword: Wirele Senor Network; Interference Alignment; Throughput; Delay. Introduction A WSN conit of a group of enor node, which are deployed in a region of interet. The enor node ene and gather information from the environment and end their data to the detination node []. The enor node cooperate to accomplih a common tak, uch a battle field urveillance and environment monitoring []. All the enor node ue a radio channel and hare the ame medium for tranmiion. During the tranmiion of a node, the other node which are in conflict with the tranmitter node cannot tranmit. There are two form of conflict: primary and econdary conflict. The primary conflict happen when a node receive more than one tranmiion or tranmit and receive in one time lot. The econdary conflict happen when a receiver R i tuned to a particular tranmitter T within the range of other tranmitter whoe tranmiion are not for R and interfere with the tranmiion of T [3]. The conflict caue packet lo, packet retranmiion, delay increment, and throughput decrement [4]. The TDMA i a good olution to avoid conflict. In the TDMA, each time lot i allocated to ome of enor node which are not in conflict with each other. For reducing the interference effect and decreaing the tranmiion delay, in [5] uing the graph coloring trategy, two centralized TDMA cheduling algorithm are developed, one node-baed cheduling and the other level-baed cheduling. In the node-baed cheduling, cheduling i obtained baed on coloring of the original network. The node of the color correponding to each lot with at leat one packet are choen firt and additional node are added afterward. In the levelbaed cheduling, the original network i tranformed to a linear network where each node correpond to a level in the original network. The cheduling of the original network i then obtained baed on coloring of the linear network. Thi cheduling algorithm chedule a nonconflicting et of node correponding to level of each color for the current lot and then chedule additional node, if poible. In TDMA, the node which interfere with each other are not permitted to tranmit imultaneouly. Thu, the tranmiion delay of packet to Bae Station (BS) increae and the throughput decreae. In thi paper, a novel method i propoed for WSN that ue interference alignment technique (IA). In the IA multiple node jointly encode their ignal to their intended receiver uch that interfering ignal are eparated and eliminated in each receiver. Thu, by applying the IA technique to WSN, the node which are within the interference range of each other and have different receiver, can tranmit imultaneouly. In propoed method, multiple et of node are elected to ue IA technique and the node of each et can tranmit by uing IA imultaneouly. However the node of each etare in conflict with each other, the propoed method provide imultaneou tranmiion. So, the centralized cheduling in the pro- Copyright 0 SciRe.

2 V. ZIBAKALAM ET AL. 9 poed method differ from network cheduling in condition that the network doen t ue IA technique. The network cheduling i done baed on a graph coloring trategy. The ret of the paper i organized a follow. Section explain the model network. Section 3 preent the IA technique. In Section 4, the IA technique in WSN i propoed. Simulation reult are given in Section 5 and Section 6 conclude the paper.. Model Network We conider a tatic WSN in which enor node periodically collect information about the environment and end their data to the BS via multi hop tranmiion. We model the WSN network by a graph G V, E where V v, v,, vn i the et of node and E i the et of wirele link among node. Each node ha a tranmiion radiu of r and an interference radiu of r. If m the node v i want to receive the meage from v j correctly, their ditance mut be le than r. The ignal of v i i interfered with the ignal of v j, if their ditance i le than r m and v j i not the intended receiver. r and r m are not necearily the ame. Typically r i maller than r m and in practice rm r 4 [6]. The conflict graph GC VC, EC i a graph in which every node repreent an edge in the original graph G and two node are connected in GC if their correponding edge are in conflict with each other in the original graph. A node i at level n if it i located at the ditance of n hop from the BS [5]. The protocol model in [7] i elected for the interference in which a packet i correctly received if no other node tranmit imultaneouly within the receiver interference range. Thi model enable the ue of graph coloringbaed cheduling algorithm []. 3. Interference Alignment The reearch on achieving imultaneou tranmiion and reception ha a long literature. In the [8], [9], the interference alignment [8] and zero forcing [9] method are addreed in which, multiple tranmitter jointly encode and end their ignal to intended receiver uch that interfering ignal are eparated and eliminated [0]. In the IA in tranmitter aligning matrice are applied to end the ignal uch that interfering ignal at each receiver lie in a ubpace which i linearly independent of deired ignal ubpace [8]. Then, the zero forcing filter i applied to the received ignal to eliminate interference ignal and retain the deired ignal. Conider a K-uer interference channel conit of K tranceiver pair in which the tranmitter U to UK end their ignal to the receiver B to BK. Each tranmitter and receiver i equipped with ingle antenna. A hown in Figure, Figure. A K-uer interference channel with K tranmitter U to U K and K receiver B to B K. each receiver only decode the ignal of it own tranmitter and the ignal of other tranmitter are conidered a interference. The deired and interference ignal are hown by olid line and dahed line, repectively. It i aumed that the full channel tate information i available at every tranmitter and receiver. The ignal Y i received by the i-th receiver can be expreed a K Y H VS H VS Z i,,,k () i ij i i ij i i i j,ji where S repreent the ignal of tranmitter i, i V i i the aligning matrix for the i-th uer, Hij repreent the channel matrix from tranmitter j to receiver i and Z i i the additive white Gauian noie with zero mean and unit variance. For perfect aligning of interference of Tranmitter to K in Receiver, we hould have H V H V H V () and in Receiver, and in Receiver i 3 3 K K H V H V H V 3 3 K K H V H V H V H V i i ii i ii i H V ik K The Equation ()-(4) can be hown a i HV HjVj 0, j, H V H V 0, j, i, i i ij j By olving (5), aligning matrice are obtained and by aligning interference ignal in each receiver, the deired ignal ubpace and interference ignal ubpace will be linearly independent. By applying the zero forcing filter W to Y at each receiver, we get for i,,,k. i i i i i ii i i i ij j j i j,j i K (3) (4) (5) Y WY WH VS WH VS WZ i (6) Copyright 0 SciRe.

3 9 V. ZIBAKALAM ET AL. where Thu, WH V j 0 j i (7) i ij Y WH VS WZ i,,,k (8) i i ii i i i i Figure how the IA olution for a 3-uer interference channel. The deired and interference ignal are preented by olid line and dahed line, repectively. The receiver of each uer only need to decode the ignal of it own tranmitter. By applying aligning matrice in tranmitter, interference ignal received at each receiver align in a one-dimenional ubpace and are linearly independent of the deired ignal ubpace. 4. Propoed Method We apply the IA technique to WSN. Applying the IA to WSN i performed in three part. Firt, we elect thoe node which make ue of the IA technique for tranmiion. In the econd part, for network cheduling we color the conflict graph GC uing a graph coloring algorithm. In the third part, network cheduling i obtained baed on graph coloring. We aume the number of enor node i N, the node which are uing the IA i NIA and the retare in the et NIA. The number of an arbitrary et member uch a B i repreented by nb and parent of an arbitrary node uch a C i repreented by PA C. n NIA n NIA N (9) 4.. Node Selection for Interference Alignment In a WSN a ingle node can both gather and forward the packet. The node tranmitting more packet, experience more trict congetion, which make delay in packet tranition to the BS. For a better performance, the IA technique i applied to the node with trict congetion. Node election ha three tage. In the firt tage, the forward degree for each node i computed. Forward degree for each node i equal to the number of node which forward their packet through that node over the routing tree. Figure 3 illutrate a network with the forward degree of node. Then, node are ordered in a decreaing degree of forward. Auming each node end at leat one packet at each tranmiion cycle, in the econd tage, we chooe the node with a high forward degree (node with degree more than 0 time of the minimum degree). In the third tage, we chooe the et of node among the elected node in the econd tage which compoe a multi-uer interference channel with their parent. It mean that the node of each et hould be within the interference range of other et node and cannot tranmit imultaneouly without IA. Thu, an arbitrary et uch a Sa noda, noda,, nodka that compoe a K-uer interference channel, hould have the following condition: ) Any two node of each et hould have different parent.,,,,, PA nod PA nod i j K i j (0) ia ja ) The parent (receiver) of each node (tranmitter) hould be within the interference range of other et node (other tranmitter). d PA nod, nod r i, j,,, K, i j () ia ja m where d i,j repreent the ditance between node i and j. 3) Each node with it parent cannot be in the ame et. if nodia Sa then PA nodia Sa i,,, K () For example, Figure 4 diplay a WSN with 000 node deployed in a circular area and the BS i located in the center of the circle. Figure 5 and 6 diplay elected node in the nd and 3rd tage, repectively. In thi example, the number of et are uing the IA i ix. The node of each et are hown in the ame color. 4.. Coloring of Network Graph For tranmiion cheduling, firt, we color the GC Figure. IA olution for a 3-uer interference channel. Figure 3. A network with forward degree of node. Copyright 0 SciRe.

4 V. ZIBAKALAM ET AL. 93 Figure 4. A WSN with 000 node. Figure 5. The elected node in the nd tage. Figure 6. The elected node in the 3rd tage. the node uing IA for tranmiion. uing a graph coloring algorithm. For thi purpoe each two node with different color cannot tranmit imultaneouly [5]. Coloring the network ha two tep. In the firt tep, we color node uing IA for tranmiion, i.e. node member of NIA. In the econd tep, we color other node in the network, i.e. node member of NIA. To aign color to the node of NIA, weform the et graph GS VS, ES with VS S, S,,SM. The node Si correpond to all node at et i and two node S and i S j are connected if there i an edge between a node at et i and any node at et j in the conflict graph of the original network. Thu, we have n S n S n S n NIA M (3) Then, the conflict degree for each node in the GS i obtained. The degree conflict of each node in the GS i equal to the number of connected edge. Then, the node in the GS are ordered in a decreaing degree of conflict and priority of coloring i given to the node with a more conflict degree. In coloring the GS, every two node conflict with each other have different color. Thu, if two et conflict with each other have different color. Since all member of a et can tranmit imultaneouly, they have the ame color. Then, the conflict degree for each node in the GS i obtained. The degree conflict of each node in the GS i equal to the number of connected edge. Then, the node in the GS are ordered in a decreaing degree of conflict and priority of coloring i given to the node with a more conflict degree. In coloring the GS, every two node conflict with each other have different color. Thu, if two et conflict with each other have different color. Since all member of a et can tranmit imultaneouly, they have the ame color. For aigning color to the node NIA, the degree conflict of each node in the GC i obtained. Then, node are ordered in a decreaing degree of conflict and the priority of color aignment i given to the node with a more conflict degree. A ome color were already aigned to the node NIA, for aigning color to node the NIA, conflict of each new node i examined with all node correponding to each color. If there i no conflict, the color i aigned to the new node; otherwie, other color hould be examined. Finally, if any color among available color i not aigned to the new node, a new color hould be aigned. The coloring algorithm i given in Figure Scheduling Network The cheduling algorithm aign one or more time lot to each node in the network for conflict-free communication uch that the delay in data collection i minimized. The network cheduling i obtained baed on graph coloring. A uper lot in our cheduling algorithm i a et of equential time lot uch that each node having one packet or more at the beginning of the uper lot end at leat one packet throughout the uperlot. All of the node allocated to the ame color can end at a time lot. The maximum number of lot in a uperlot i the total number of color utilized for coloring the network. After determining the node correponding to the current time lot, a long a the reulting et i non-conflicting extra node allocated to other color are added. The propoed method i practical for actual tatic WSN, which in the location of node are fixed, becaue the node election part of the propoed method i Copyright 0 SciRe.

5 94 V. ZIBAKALAM ET AL. i S,S,,S N M VC,EC VS,ES V,C, V,C,, V,C N N or Input : VS V, V,, V, VS Conflict graph GC et graph GS Output : C,,, Z Z : number of col Coloring node uing IA begin ort the et a conflict degree a IA, IA,, IA M for k to M i while j allocated to color i t. j, IA ES i i end allocate color i to IA k allocate color i to et member IA k end end k Coloring node don t ue IA begin ort the node a conflict degree a n, n,, n for t to nnia i while j allocated to color i t. j, n EC t i i end allocate color i to n t end end nnia radiu 00 and 00 i. We ue Dijktra algorithm a hortet path routing to determine the routing tree rooted at the BS. The reult preented here are the average performance of 00 different network realization. The reult of imulation are compared to two TDMA cheduling algorithm, one node-baed and the other level-baed [5]. Figure 8 and 9 repectively diplay the delay and average throughput of the propoed method in comparion with the TDMA cheduling algorithm veru for rm r, repectively. A the imulation how, by uing propoed method, the delay greatly reduce and throughput ignificantly increae. Thi happen ince in TDMA without uing IA, the node which are within the interference range of each other cannot tranmit imultaneouly cauing the delay to increae and throughput to decreae. In contrat, while IA i ued, thee node can tranmit imultaneouly. Hence, the number of concurrent tranmiion increae leading the delay to decreae and throughput to increae. Alo, the imulation reult demontrate that the performance of the propoed method depend on thenetwork topology. Figure 0 how the percentage of performance improvement (PPI) of the propoed method with repect to node-baed and level-baed algorithm veru Figure 7. The coloring algorithm. done once uch that thi part i not required for each data collection cycle. In other word, the node election part load no additional delay during the tranmiion. Other two part of the propoed method have imilar computational complexity to the node-baed and level-baed cheduling algorithm. 5. Simulation Reult For evaluation of the propoed method, we ue two metric; the delay and throughput. The delay i the time duration in which all packet generated by all node reach the BS. The throughput i the average rate of ucceful data delivery over the channel and it i meaured in data packet per time lot. In imulation, the WSN conit of 000 enor node randomly ditributed within a circular area with radiu of 00 unit. The BS i located in the center of the circular area. The denity of enor node within the radiu 00 i and between the Figure 8. Comparion of delay of propoed method with thoe of node-baed and level-baed algorithm. Figure 9. Comparion of throughput of propoed method with thoe of node-baed and level-baed algorithm. Copyright 0 SciRe.

6 V. ZIBAKALAM ET AL. 95 Figure 0. Percentage of delay performance improvement of propoed method with repect to node-baed and levelbaed algorithm for different ratio.. In Figure 0, by increaing the ratio, the PPI increae to a certain value and afterward decreae. Therefore, for rm r, the propoed method preent a good PPI in topologie with the medium ratio and a lower PPI in the topologie with low and high ratio. Thee change are due to dependency of the propoed method performance on two factor: ) Interference degree of elected node in nd tage degt : the interference degree for each node i the number of node interfere that with it. With increaing degt, the number of node NIA increae cauing improvement in propoed method performance becaue the proportion of packet tranmitted by node NIA to that of node NIA increae. ) The difference between forward degree of node NIA and NIAdiffAA : With increaing diffaa, the performance of the propoed method improve becaue the proportion of packet tranmitted by node NIA to that of node NIA increae. With increaing, degt increae while diffaa decreae. Up to a certain amount of, influence of degt increment i predominant and afterward influence of diffaa decrement become predominant. Figure -3 how the impact of interference radiu on performance of thee method. Thee figure how the delay of the method veru r m r for three ratio of a follow: 9, repreent a topology in which the denity of packet i higher at the upper level of the routing tree., repreent a topology in which the denity of packet i equal throughout the network. 9, repreent a topology in which the denity of packet i higher at the lower level of the routing tree. Reult how that with increaing the rm r ratio, the delay i increaed, becaue the number of the node Figure. Comparion of the delay of propoed method with node-baed and level-baed algorithm veru r m r for 9. Figure. Comparion of the delay of propoed method with node-baed and level-baed algorithm veru r m r for. Figure 3. Comparion of the delay of propoed method with node-baed and level-baed algorithm veru r m r for. 9 which interfere with each other increae and the number of concurrent tranmiion decreae reulting in a decreaed tranmiion rate and an increaed delay. Figure 4 how the PPI of the propoedmethod with re- Copyright 0 SciRe.

7 96 V. ZIBAKALAM ET AL. pect to the node-baed algorithm veru r m r. In Figure 4, by increaing rm r ratio for the topologie with the medium or high ratio, the PPI increae while for the topologie with low ratio, the PPI increae to a certain value and afterward decreae. Figure 5-7 diplay the average throughput of thee method veru r m r for three value of, repectively. Simulation reult how that the propoed method perform better in topologie with the ame ratio of and. Thi happen ince in topologie with the medium ratio, both degt and diffaa i high while in topologie with low ratio, deg t i low and in topologie with high ratio, diff AA i low. 6. Concluion We applied the IA technique to WSN to reduce interference effect. In thi way, multiple tranmitter jointly encode their ignal to intended receiver uch that interfering ignal are eparated and eliminated at each Figure 6. Comparion of the throughput of propoed method with node-baed and level-baed algorithm veru r r for. m Figure 7. Comparion of the throughput of propoed method with node-baed and level-baed algorithm veru r r for. m 9 Figure 4. Percentage of delay performance improvement of propoed method with repect to node-baed algorithmfor different rm r ratio. Figure 5. Comparion of the throughput of propoed method with node-baed and level-baed algorithm veru r r for 9. m receiver. By applying the propoed methodto WSN, delay and throughput performance ignificantly improve. The performance of the propoed method depend on the network topology. Compared to the topologie with low and high ratio, in the topologie with the medium ratio, the percentage of performance improvement in the propoed algorithm i more. REFERENCES [] H. Choi, J. Wang and E. A. Hughe, Scheduling for Information Gathering on Senor Network, Wirele Network, Vol. 5, No., 009, pp doi:0.007/ [] J. Zheng and A. Jamalipour, Wirele Senor Network: A Networking Perpective, John Wiley & Son, Inc., Hoboken, 009. [3] L. Paradi and Q. Han, TIGRA: Timely Senor Data Collection Uing Ditributed Graph Coloring, Proceeding of the 6th Annual International Conference on Per- Copyright 0 SciRe.

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