IEEE COMMUNICATIONS LETTERS, VOL. 12, NO. 8, AUGUST 2008
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How to Tune VoIP Codec Selection in WLANs? Anna Sfairopoulou, Boris Bellalta, and Carlos Maci´an
Abstract—In IEEE 802.11e-based WLANs, Link Adaptation mechanisms, which choose the transmission rate of each node, provoke unexpected and random variations on the effective channel capacity. When these changes are towards lower bitrates, inelastic flows, such as VoIP, can suffer from sudden congestion, which results on higher packet delays and losses. A VoIP codec selection algorithm has been proposed as a solution to this issue, which is triggered both by channel rate changes as well as in combination with a call admission control mechanism. The results show that an important improvement in terms of hotspot capacity for VoIP calls can be achieved by choosing the VoIP codec adaptively in a multi-rate scenario. By defining a new Grade of Service-related parameter, Q, which captures the tradeoff between dropping and blocking probabilities and perceived speech quality, the codec selection algorithm can be tuned to achieve maximum capacity without severely penalizing any of those variables, and hence satisfying both technical and user quality requirements. Index Terms—VoIP, multi-rate WLANs, QoS, codec adaptation.
I. I NTRODUCTION
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OIP over WLANs could be a killer application in cooperation with 3G mobile networks. However, WLANs are not designed to carry VoIP (or any other inelastic traffic flow) and consequently there are several factors resulting in low call capacity (number of simultaneous active calls). One of the most important factors is the effect of the Link Adaptation mechanism of 802.11, causing what is also known as a multi-rate channel. In this channel, one user changing its transmission rate provokes a capacity variation of the wireless channel with visible effects for all active calls, like increased delay and packet losses [1]. To solve this problem, a codec adaptation algorithm was presented in [1], which adapts the VoIP codec to the hotspot state (number of calls, channel conditions for each call, etc.) in order to avoid dropping active calls. Additionally, in order to also maximize the number of new call requests accepted in a generic wireless network, a combined Call Admission Control with Codec selection (CAC/CS) algorithm was proposed in [2], based on applying joint decision policies. In this letter the performance of the CAC/CS algorithm is evaluated, as a function of the adaptation scope. Three cases are studied: Adapt only at the occurence of rate changes, adapt only at new call requests, or both. Some of the generic decision policies presented in [2] are examined here for the specific case of IEEE 802.11b/e [3] hotspots. Moreover, since
Manuscript received November 27, 2007. The associate editor coordinating the review of this letter and approving it for publication was C. Douligeris. The authors are with the Departament de Tecnologies de la Informaci´o i Comunicacions (DTIC), Universitat Pompeu Fabra, Barcelona, Spain (e-mail:
[email protected]). Digital Object Identifier 10.1109/LCOMM.2008.071998.
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most existing terminals are very limited in their capabilities and hence cannot support the computational burden of using certain (more complex) codecs, heterogeneous terminals have been considered, taking their computational power as the limiting factor to constrain the set of available VoIP codecs for every one of them. The results show clearly how the adaptive policies outperform the static ones. However, blindly using adaptive policies could increase the capacity of the hotspot (i.e., minimize dropping and/or blocking probabilities) at the expense of perceived call quality (e.g. as characterized by the Mean Opinion Score or MOS). As shown later, using a well-balanced mixture of these three criteria allows for an increase in capacity while keeping an adequate call quality in all cases. II. P OLICY-BASED C ODEC S ELECTION IN WLAN H OTSPOTS When a new call request or a rate change in an active call is detected, the CAC/CS scheme is triggered. Then, the CAC/CS evaluates the new (forecasted) system state. If the new state is deemed unsustainable (i.e., the hotspot’s effective bandwidth is lower than the requested traffic load), a new combination of VoIP codecs for each active call (φ) is suggested, based on a predefined policy (i.e., the set of rules about which calls shall adapt their codec and in what order). These policies are explained later in this section and the joint CAC/CS scheme is shown in Figure 1. The system state is defined by the number of active calls nv , the set of channel rates R for every call, the set of VoIP codecs in use C (which includes information about the bandwidth, packet length and processing power required by each codec in MIPS –Million of Instructions per Second) and the processing power constraint ζm of each mobile node, which reduces the set of usable codecs to those which satisfy that ζ(c) ≤ ζm , where ζ(c) is the processing power required by codec c, with
c 2008 IEEE 1089-7798/08$25.00
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IEEE COMMUNICATIONS LETTERS, VOL. 12, NO. 8, AUGUST 2008
c C. Notice that lower bit-rate codecs, like G.729A and G.723.1, may consume fewer cell resources offering also high MOS but come with the counterpart of high complexity, which is translated to higher processing cost for the node. A. Non-Adaptive Policies Under a fixed-codec policy, each call maintains the initial codec throughout its duration. No codec adaptation is performed and when any congestion occurs a simple drop/block solution is applied. Two policies have been considered in this category: • P1: Start with lowest bandwidth codec. All calls enter the network with the lowest bandwidth codec present in C if ζ(c) ≤ ζm and the available cell capacity can support it (otherwise the call is blocked). This policy allows a higher number of active calls (due to less bandwidth demand from each) but with the counterpart of the lowest MOS. Additionally, a high number of calls/nodes are blocked due to their inability to support the high complexity of this codec. • P2 : Start with highest codec. This policy will provide the best average MOS at the expense of an expected higher blocking and dropping rate, since each call requires the highest amount of bandwidth. Notice that all mobile nodes will support this codec. B. Adaptive Policies In this category, all new calls always request service using the highest bandwidth codec. However, in order to allocate space for new calls or to solve the channel congestion caused by rate changes, any number of calls can be requested to change their current codec to a lower one (c ), if it is supported by the mobile node (it satisfies that ζ(c ) ≤ ζm ). It is the most complex solution but also the one that gives best results in terms of dropping and blocking rate. There are different criteria that can be used to select which calls have to suffer a VoIP codec degradation. For the sake of simplicity and due to space restrictions only one possibility is presented here: Choose the next call for adaptation randomly. • P3: Change randomly: In this method, the next call to suffer a codec change is chosen randomly from all the active calls on the cell. If this call can not switch to a lower codec, the algorithm will choose a new one. This process is repeated until the congestion is solved or until all active calls have been checked. Since the CAC/CS module keeps complete information about the cell and its calls, it iteratively performs the calculations stated above, as well as computing the resulting cell state, prior to actually triggering the codec changes. Hence, if no feasible solution is found, the problematic call will be dropped or blocked, without affecting the others. III. D ISCUSSION OF THE A DAPTATION I MPACT ON OVERALL C APACITY AND Q UALITY I MPROVEMENT A scenario which consists of an IEEE 802.11b/e hotspot that includes a QoS-enabled AP (QAP) and a number of QoS-enabled mobile stations (QSTA) is considered. Only
TABLE I C ODECS PARAMETERS Codec G.711 G.726 G.729A G.723.1
C=[G.711, G.276, G.729, G.723.1] Bit-rate (B) Packet size (L) Complexity (ζ) 64 Kbps 160 B 1 MIPS 32 Kbps 80 B 10 MIPS 8 Kbps 20 B 15 MIPS 5.3 Kbps 20 B 25 MIPS
MOS 4.1 3.85 3.7 3.6
VoIP traffic is present in the cell, with call requests arriving with rate λ and with call duration following an exponential distribution with mean equal to 1/μ = 240 seconds, so that the traffic load A varies from 1 to 50 Erlangs. A frequency γ of 1/100 rate changes per second and mobile node is considered and the available set of rates is R = [11, 5.5, 2, 1] Mbps. A C++ simulator has been implemented based on the COST simulation toolkit [4]. The hotspot capacity is forecasted using a process similar to the one described in [5] but modified for the multi-rate/multi-codec scenario. The basic parameters considered for the codecs are shown in Table I. In addition, the computational cost of the codecs under study has been considered. Each node has been randomly assigned a maximum processing power ζm with a uniform distribution between 1 and 40. This means that a significant portion of the terminals can not implement all codecs due to lack of processing resources, a situation still common nowadays1. Three combinations of the CAC/CS algorithm were tested, and blocking (Fig. 2.a) and dropping (Fig. 2.b) probabilities as well as the E[M OS] in the cell (derived from the theoretical values associated with each codec) (Fig. 2.c) were obtained for each case and policy. From the figures, the following main lessons can be drawn, concerning the three cases mentioned before: (i) Apply codec selection only to new call requests and drop any call provoking congestion due to a changing rate: This case shows a low blocking probability, a high dropping probability (since no adaptation is applied) and an E[M OS] highly dependent on the offered traffic load. (ii) Apply codec selection only in presence of rate changes and use a simple CAC for new calls (block any call that cannot fit in): This second case provides a high protection for the already accepted calls (very low dropping probability) at the cost of blocking a high number of new call requests. The E[M OS] is maintained at high values in spite of higher offered traffic load. (iii) Apply codec selection both for new calls and at any rate change causing congestion: A trade-off between blocking and dropping probabilities is achieved. However, it shows the worst E[M OS] values similar to case (i) as this case allows the highest number of codec adaptations. From the analysis above it becomes clear that there is a trade-off between blocking and dropping rate and voice quality (MOS value). Thus, in order to decide where and 1 It is expected that technological evolution will ameliorate this situation in the next years even for the simplest terminals. However, the effect of more powerful terminals, as explained later, is simply to increase the effectiveness of the adaptation process described here.
SFAIROPOULOU et al.: HOW TO TUNE VOIP CODEC SELECTION IN WLANS?
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increase) without heavily impacting the dropping and blocking probabilites: Hence the low Q values. However, under heavy load conditions, there is less margin for adaptation and so the best solution to keep all three metrics in check is to change codec only as a response to rate changes, in order to guarantee a low dropping probability for the already accepted calls2 .
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when to use Codec Selection depending on the traffic load, a new GoS (Grade of Service) factor which combines the above metrics is needed. This ”Quality and Quantity” factor, called Q (complementary, as the goal is to minimize it), can provide a combination of blocking (B) and dropping rate (D) as quantitative metrics, with the average normalized MOS value in the hotspot as a speech quality metric. It is calculated as Q = α(1 − M OSn ) · (B + 10 · D)
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where M OSn is the normalized MOS between 0 and 1 and computed from M OSn = E[M OS]/M OSmax with M OSmax = 5. Notice that E[M OS] could be computed easily in real time (for example, using the E-model). Here, α is simply a scaling parameter to maintain the Q similar to those values provided by the usual GoS definition in cellular networks [6]. In Figure 3 the Q-factor values of the studied policies are plotted. In general, a cell under low traffic conditions (in our case A ≤ 5 Erlangs) has the flexibility to permit codec modifications, so as to try to accept more new calls (overall capacity
In this letter we have seen the results of applying codec selection in multi-rate WLANs under different policies. The results have shown how the utilization of adaptive codec selection policies increase the performance of the WLAN in terms of higher capacity (calls which are accepted and finished correctly, i.e. lower blocking and dropping probabilities) but also based on the perceived speech quality. By re-uniting all three important metrics in one new GoS parameter, Q, a simple yet effective tool for optimizing the adaptation process is provided. R EFERENCES [1] A. Sfairopoulou, C. Macian, and B. Bellalta, “VoIP codec adaptation algorithm in multirate 802.11 WLANs: distributed vs. centralized performance comparison,” Lecture Notes in Computer Science, vol. 4606, pp. 52–61, 2007. [2] B. Bellalta, C. Macian, A. Sfairopoulou, and C. Cano, “Evaluation of joint admission control and VoIP codec selection policies in generic multirate wireless networks,” in Proc. ITC/IEEE NEW2AN’07, St. Pertersburg, Russia. [3] I. S. 802.11e, “Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) specifications; amendment: Medium Access Control(MAC) quality of service enhancements,” IEEE Std 802.11e, 2005. [4] G. G. Chen, “Component Oriented Simulation Toolkit,” http://www.cs.rpi.edu/ cheng3/, 2004. [5] D. P. Hole and F. A. Tobagi, “Capacity of an IEEE 802.11b Wireless LAN supporting VoIP,” in Proc. IEEE International Conference on Communications (ICC’04), Paris, France, June 2004. [6] S. A. AlQahtani and A. S. Mahmoud, “Dynamic radio resource allocation for 3G and beyond mobile wireless networks,” Elsevier Computer Commun. vol. 30, pp. 41-–51, Aug. 2006. 2 If the terminals could support all codecs due to increased processing power, they could benefit from higher adaptation flexibility. Consequently, the main effect would be to shift the curves to the right, i.e., to increase the ”low traffic” section up to some 15 Erlangs for a maximum processing power in the terminals of 100 MIPS.
