Scheduling for VoIP Service in cdma2000 1x EV-DO

Transcription

1 Scheduling for VoIP Service in cdma2000 1x EV-DO Young-June Choi and Saewoong Bahk School of Electrical Engineering & Computer Science Seoul National University, Seoul, Korea {yjchoi, Abstract Recently cdma2000 1x EV-DO (HDR) system has begun to be deployed in some countries to support high data rate services in cellular networks. The system is originally designed to support data services, but now is expected to serve some real-time traffic including VoIP. For VoIP service with delay bound and low loss requirements, we propose a frame structure considering delay bound and a scheduling algorithm reflecting channel conditions. To schedule VoIP, we adopt the maximal rate algorithm and the proportionally fair algorithm. The proportionally fair algorithm (PF) was known to be appropriate for elastic traffic, however, from simulation results, we conclude that the PF algorithm with the channel test is an appropriate scheduling scheme to provide QoS of VoIP. When the required slot portion of VoIP is 75%, the loss rate is about 1% on the average and 3% in the worse case. On the other hand, the maximal rate algorithm shows twice of the loss rate for the same delay bound and load. Additionally we propose a simple admission control scheme for VoIP service that controls the average portion of slots occupied by VoIP packets. I. INTRODUCTION Traditionally cellular systems have been used to provide circuit-based voice calls. Since a lot of data services have been available in Internet and the demand for wireless service is accordingly increased, cellular networks have begun to deploy high data rate systems such as cdma2000 1x EV-DO [1]. The high data rate systems have an important meaning because next generation communication systems are expected to be based on all-ip architecture and support some real-time services integrated by packet data. In the CDMA voice network such as IS-95, a sender controls the transmission power to receive required quality of service (QoS) at the frame level. The quality of a call is influenced by the signal power from all other users and base stations (BSs) which become interference to its own signal. However, to support high data rates, cdma2000 1x EV-DO controls the transmission rate instead of power and also allocates one downlink channel multiplexed by time division instead of code division to each BS. The conventional downlink scheduling in cdma2000 1x EV- DO uses proportional fairness in order to utilize the varying channel conditions effectively [9]. The scheduling scheme is known to be appropriate for data packets, while on the other we cannot apply the scheduler to VoIP packets with delay bound and low loss requirements because the proportionally fair scheduling does not consider QoS like delay and loss. Therefore we developed a proper scheduling method for VoIP service applicable to cdma2000 1x EV-DO. Some previous works discussed the delay issue for scheduling. [2] proposed SRPT(Shortest Remaining Processing Time) scheduling to guarantee the shortest average delay but it might cause some jobs to starve. Alternatively [3] used the concept of stretch, a kind of normalized delay. [4] showed some results using SRPT and stretch-based algorithm in CDMA data networks. More recent papers have focused on maximizing revenue [5], [6]. We already proposed utility-based QoS scheduling using the concept of opportunity cost in [7]. There is, however, few related works about QoS issues in such packet cellular systems as cdma2000 1x EV-DO. In this paper, we design a new frame structure to meet the delay bound of some services and show that the proportionally fair scheduling within the frame structure works well for contending VoIP packets. Section II describes the considered system and Section III explains required QoS for VoIP and proposes a frame structure. Then we present conventional scheduling algorithms and applies them to our frame structure in Section IV. Section V shows performance comparison results through simulations and Section VI discusses a simple call admission control algorithm by using the results. Finally Section VII concludes this paper. II. SYSTEM DESCRIPTION A. Physical Layer in Wireless Link Referring to the specification of cdma2000 1x EV-DO system [1], we can summarize the properties of downlink channel as follows. First, the downlink channel is a single broadband link shared by all users in a cell and one user is allowed to transmit data in a time slot. Second, the BS estimates the channel condition by using the measurement fedback from the mobile terminal and transmits at a fixed power. Third, adaptive modulation and coding schemes are adopted to support various data rates with reliable transmission. Table I which shows parameters for adaptive modulation and coding indicates that the number of required slots for the normalized bits increases inversely proportional to the data rate. That is, the amount of time for transmission increases when the channel condition gets worse. The specification of cdma2000 1x EV-DO also suggests 4-slot interlacing scheme for time diversity. For example, a

2 TABLE I PARAMETERS FOR MODULATION AND CODING IN CDMA2000 1X EV-DO DOWNLINK Data Rate(kbps) Slots Bits Code Rate Modulation /4 QPSK /4 QPSK /4 QPSK /4 QPSK /4 QPSK /4 QPSK /4 QPSK /2 QPSK /8 8-PSK /2 8-PSK /2 16-QAM /2 16-QAM packet of 1024bits with 76.8kbps uses 8 slots. Conventionally the 8 slots may be successive, while, in 4-slot interlacing scheme, they are transmitted every 4 slot and other packets are also transmitted between these slots in a similar pattern. In this paper, however, we do not consider 4-slot interlacing scheme and just assume that every packet requiring multislot is continuously transmitted because we focus on the scheduling scheme and 4-slot interlacing is easily applicable to our scheme. B. Network Architecture for VoIP As we focus on the downlink, we consider the case that a user with a wired terminal or telephone tries to call some other mobile user. Fig. 1 shows the network architecture generally used for VoIP service and the arrows in Fig. 1 indicate the call flow. The voice signal generated at a transmitter forms IP packets by using an encoder and a packetizer. The encoder periodically samples the original voice signal and makes a constant bit rate stream. The bit rate is decided by the type of an encoder. For example, G.711 traditionally used in PSTN creates 8bits sample per 0.125ms, leading to 64kbps. For bandwidth-limited networks, encoders support rate reduction at the expense of lower quality. G.729 used in our simulation provides 8kbps and furthermore G provides a lower rate of 6.4kbps. The data rate can be reduced by voice activity detection which adapts to the duration of talkspurt and silence. However, we do not consider it because the null packet (only with header) generated during the silence period is also large enough compared to a talkspurt-packet when the rate is low. The packetizer encapsulates voice samples into packets of equal sizes and attaches the RTP header. Then the packets are delivered to the receiver through the IP network. Before proceeding to the depacketizer and the decoder in the receiver, playout buffer plays a role of absorbing delay jitter by buffering arrived packets. The delay bound of playout buffer is crucial to the QoS performance. To adapt the playout delay to the varying network delay, some previous works have used adaptive playout schemes [10], [11]. III. QOS PROVISION FOR VOIP SERVICE A. QoS Issues For VoIP service, we need to design a QoS provision from the viewpoint of a user s application-layer level. To measure the QoS of a voice call, a commonly used metric is MOS (Mean Opinion Score) and Emodel [12]. While MOS rates the quality averagely on a scale from 1 to 5, Emodel quantizes the quality more specifically on a scale from 0 to 100. The value of Emodel is written by R = R o I d I E (1) where R o includes the total rating reflecting the effects of noise and intrinsic factors. I d and I E are respectively decided by the effects of delay and distortion over the network. As the parameter estimation is beyond our concern, we will not mention it any more. We derive two QoS metrics from the model - delay and loss, and deal with them over a wireless link because it becomes a bottleneck often. B. Frame Structure To guarantee the delay in the wireless link, we design a new frame consisting of a certain number of slots. Fig. 2 shows the basic frame structure with 24 slots. We allocate the first part of the frame denoted as G to VoIP packets for priority service. Then the residual part is distributed to normal data packets which do not require urgent delivery. As VoIP packets arrived during one frame time will be transmitted in the next frame, the number of G may be changeable according to the channel condition. If a VoIP packet arrived during the prior frame cannot be transmitted, it will be dropped. Therefore the delay at a BS, D BS, has an upper limit, D BS T slot (N + G) 2T slot N (2) where N is the frame size and T slot is the slot length in a time. We also need an admission control scheme so that the average of G may not be larger than N or predefined value, which we will mention in Section VI. Telephone IP network Cellular phone N Wired terminal Wireless terminal Voice source Encoder Packetizer... Scheduler Playout buffer Depacketizer Decoder Voice source G N-G Fig. 1. Network architecture for VoIP. Fig. 2. Frame structure.

3 Test availability : if(slot num + slot K N & DRC k D min) return 1 Test selection : MAX selection : X max DRC max, X k DRC k PF selection : X max DRC max/r max, X k DRC k/r k if(x max < X k (X max = X k & prob 0.5)) return 1 Initialize frame : slot num 0 T {every voice session with packets to transmit} End frame : Drop packets of each session T Fig. 3. Pseudo code of functions. The delay depends on N very much. As N increases, the delay gets longer but the loss rate becomes lower. On the contrary, if N is too small, the number of VoIP users that can be accommodated is limited. Therefore, considering the endto-end delay, we need to have N as small as possible only if the service is feasible. If we adopt 4-slot interlacing for time diversity, the frame structure only needs to change the service order. Thus the proposed frame structure can be applied to cdma 1x EV-DO system if N is a multiple of 4. IV. SCHEDULING STRATEGY We used two basic algorithms for scheduling VoIP packets. One is the maximal rate algorithm (MAX) which selects a user with the maximal transmission rate. The other is the proportional fairness algorithm (PF) which was shown to be appropriate for elastic best-effort traffic. We divided each scheduler into two categories according to service flexibility and denote them as hard and soft scheduling, respectively. Accordingly there are four algorithms, which are represented as,,, and, respectively. A. Maximal Rate Algorithm The transmission data rate varies according to the channel condition. Hence scheduling a user with the maximal rate can be a good choice to improve the whole performance. The algorithm can be written as k (n) = arg max R k (n). (3) k where k represents the user index and R k (n) is the rate of user k at slot n. The purpose of the algorithm is max T k (n) (4) n where T k (n) is the user k s throughput at slot n. However, this algorithm has a problem of fairness because the scheduler may not allocate slots to users whose channel condition is bad. Though, we cannot use max-min 1 : while(slot num < N) 2: X max NULL, selected NULL, S NULL 3 : for every voice session k T 4: if(t est availability(k) =1) 5: S S {k} 6: if( T > 0) 7: forevery voice session k S 8: if(t est selection(k) =1) 9: X max X k, selected k, T T {k} 10 : else 11 : for every active data session k 12 : if(t est availability(k) = 1&T est selection(k) = 1) 13 : X max X k, selected k 14 : slot num slot num + slot selected 15 : scheduling selected Fig. 4. Pseudo code of hard scheduling algorithms. fair scheduling because it seriously deteriorate the whole performance. Alternatively we consider proportional fairness for VoIP packets. B. Proportionally Fair Algorithm Proportional fairness is defined as a solution of X for max( i x i). A proportional fair allocation has the property that for any other feasible allocation (x 1,..., x n), the aggregate of proportional changes is nonpositive, i.e., i (x i x i)/x i 0 [8]. We can state the meaning of proportional fairness as follows. If we use another scheduling algorithm to increase the throughput of a certain user by y% over that user s throughput under the proportional fair scheduling algorithm, the summation of all the percentage decreases of throughputs suffered by all the other sessions under the new algorithm should be more than y%. To enhance the throughput in the HDR system, [9] suggests to use proportional fair scheduling. Let R i (t) be the estimate of the average data rate for user i at slot t, and the current requested data rate from user i be DRC i (t). Then in order to satisfy the proportional fairness, the user with the highest ratio of DRC i (t)/r i (t) out of all active users will have the right for transmission at time t. That is, k = arg max DRC k (t)/r k (t). (5) k R i (t) is updated as following. { (1 1 t R k (t+1) = c )R k (t)+ 1 t c DRC k (t) if allocated, (1 1 t c )R k (t) if not allocated, (6) where t c is the averaging factor of low pass filter. C. Hard and Soft Algorithms In the two above scheduling algorithms, we allocate VoIP packets to the first part of a frame and best-effort packets to the second part. This gives absolute priority to VoIP packets over data packets so we call this the hard algorithm which is

4 Test channel : if(drc k R k) return 1 Fig. 5. Pseudo code of a function appended for soft scheduling. 4: if(t est availability(k) =1)&T est channel(k) =1) 6: if( T > 0& S > 0) Fig. 6. Modified part of pseudo code for soft scheduling algorithms. shown in Fig. 4. Fig. 3 describes functions common to each algorithm. We also introduce another strategy for flexible scheduling. When the feasible data rate of a specific VoIP session is lower than the average value due to the bad channel condition and all VoIP packets left experience the same condition, the scheduler may give the turn to some other data sessions as shown in Fig. 7, which we name it the soft algorithm. Since we can get the information about the average data rate, R k (t), frompf scheduling, the soft algorithm is easy to run. Fig. 5 and Fig. 6 show the appended function and the pseudo code of soft scheduling, respectively. V. PERFORMANCE EVALUATION For simulations we consider a cluster of seven hexagonal cells with a center cell. The six neighboring cells generate the interfering signal to the center cell. We assume that users location is uniformly distributed within the cell. The data rates shown in Table I are used. The channel model is assumed to follow the Rayleigh fading with the mobility of 3km/h and the path loss exponent of 4. Other used parameters are given in Table. II which includes the VoIP source model using G.729. We focus on the performance at the center cell with Drop Probability(%) Drop probability(%) Fig Fig. 8. Number of voice sessions Average drop probability of VoIP packets User ID. Drop probabilities of 5 users suffering worst performance. N Fig. 7. Modified frame by soft algorithm. TABLE II PARAMETERS FOR SIMULATION EVALUATION Parameter Value bandwidth 1.25MHz cell radius 1,000m simulation time 240,000slots slots in a frame 24 slot length 1.667ms averaging factor for PF (t c ) 1,000 BS transmission power 20W packet length of VoIP 40bytes interval of VoIP generation 40ms the increase of the number of VoIP sessions from 8 to 14. Additional 10 more sessions are assumed to always have data packets to transmit. For simplicity, we consider delay and loss at the wireless link. To evaluate the performances of our proposed four algorithms, we compared them with conventional proportional fair scheduling () which does not give priority to VoIP packets. First, Fig. 8 shows the drop probability of VoIP packets. The drop probability increases as the traffic load goes high. One interesting result is that the drop probability of hard scheduling is higher than that of soft scheduling in both MAX and PF scheduling. The hard scheduling gives absolute priority to VoIP packets over data packets, while the soft scheduling tests the channel condition. It shows that the scheme considering the channel condition performs better than the absolute priority scheme without channel test. Thereby, the soft scheduling enables more VoIP packets to be serviced by lowering the drop probability. Fig. 9 shows that, while results in large variation of the drop probability, our proposed and

5 Slot Portion of Voice(%) Number of voice sessions Avg. number of voice slots required in a Frame Distance of a user from the BS (m) Fig. 10. Slot Portion of VoIP packets. within the frame structure show better performance than MAX scheduling in terms of the worst case drop probability. Fig. 10 depicts the slot portion of VoIP packets over the total traffic. The portion in is less than that in the other schemes because does not differentiate VoIP service. Meanwhile, the portion in the MAX is higher than in the PF, because, for the same amount of slots, the PF scheduler can accommodate more users than the MAX scheduler. Lastly, Fig. 11 shows the required number of slots to support a voice user according to the distance from the BS when the minimum number is one. As shown in Table. I, the number of slots to transmit normalized unit packet increases as the data rate decreases. Overall the scheduler shows the best performance in terms of QoS and efficiency. VI. DISCUSSIONS As evaluated in Fig. 8, the drop probability of VoIP increases with the number of VoIP sessions. Therefore we need to apply an admission control to our scheme to meet predefined QoS profile. For instance we can consider an admission control scheme satisfying S k,avg + S new,voice S total,voice (7) k T where S k,avg is the average amount of slots used by current sessions as in Fig. 10 and S new,voice is the estimated average amount of slots for a new session by the channel information as in Fig. 11. The system admits a new voice session only if the total amount of slots, S total,voice in (7), used by existing sessions (group T) plus the new session is less than the value given by predefined QoS profile. VII. CONCLUSION The deployment of data service in cellular networks has brought a new data system such as cdma2000 1x EV-DO. In this paper, for the VoIP service in packet data cellular systems, we developed a simple frame structure that can accommodate the delay bound and evaluated some possible scheduling algorithms such as the maximal rate and proportionally fair algorithm. The proportional fairness was known Fig. 11. Required slots according to the distance from the BS. to be an appropriate scheduling criterion for elastic traffic. In our simulation for VoIP, given the delay bound with our frame structure, the proportionally fair scheduling showed good performances; the efficiency of slot utilization, and the low loss rate both on the average and in the worst case. In order to consider the channel condition, we used the soft algorithm, under which even a VoIP session should pass a test if the current data rate is larger than or equal to the average data rate. In conclusion, proportionally fair scheduling combined with soft algorithm () showed the best result. However, there remains another problem of proportionally fair scheduling requiring an exact estimation of the average data rate, which is left for a future work. REFERENCES [1] 3GPP2 C.S v4.0, cdma2000 high rate packet data air interface specification, October [2] D. Karger, C. Stein, and J. Wein, Handbook of algorithms and thoery of computation, CRC Press, [3] M. Bender, S. Chakraborti, and S. Muthukrishman, Flow and stretch metrics for scheduling continuous job streams, Proc. IX Ann. ACM- SIAM Symp. Discrete Algorithms, pp , San Francisco, U.S., January [4] N. Joshi, S. Kadaba, S. Patel, and G. Sundaram, Downlink scheduling in CDMA data packets, ACM MOBICOM 2000, Boston, U.S., August [5] P. Marbach and R. Berry, Downlink resource allocation and pricing for wireless networks, IEEE INFOCOM 2002, New York, June [6] M. Agarwal and A. Puri, Base station scheduling of requests with fixed deadlines, IEEE INFOCOM 2002, New York, U.S., June [7] Y. Choi and S. Bahk, QoS scheduling for multimedia traffic in packet data cellular networks, IEEE ICC 2003, Anchorage, U.S., May [8] F. Kelly, A. Maulloo, and D. Tan, Charging and rate control for elastic traffic, European Transactions on Telecommunications, vol.8, pp.33-37, [9] A. Jalali, R. Padovani, and R. Pankaj, Data throughput of CDMA-HDR a high efficiency-high data personal communication wireless system, IEEE VTC-Spring 2000, Tokyo, Japan, May [10] R. Ramachandran, J. Kurose, D. Towsley, and H. Schulzrinne, Adaptive playout mechanisms for packetized audio applications in wide-area networks, IEEE INFOCOM 1994, Toronto, Canada, June [11] S. Moon, J. Kurose, and D. Towsley, Packet audio playout delay adjustment: performance bounds and algorithms, ACM/Springer Multimedia Systems, vol.6, pp.17-28, January [12] ITU-T Recommendation G.107, The Emodel, a computational model for use in transmission planning, December 1998.