Assessing Call Quality of VoIP and Data Traffic over Wireless LAN

Transcription

1 Assessing Call Quality of VoIP and Data Traffic over Wireless LAN Wen-Tzu Chen and Chih-Yuan Lee Institute of Telecommunications Management, National Cheng Kung University, No. 1 University Road, Tainan 701, Taiwan, wtchen@mail.ncku.edu.tw Abstract In this paper, we evaluate the quality of speech over a wired-cum-wireless scenario with the presence of various non-voip flows by simulations. The quality is mainly determined in terms of network impairments (e.g. one-way delay, jitter and packet loss). Besides, Mean Opinion Score (MOS) and E- Model defined by ITU-T are also employed to assess call quality. In the experiments, it is essential for us to present the difference between a variety of codecs (e.g. G.711/G.723.1/iLBC) with the help of some impairments and understand the maximum number of voice calls for different codecs in b wireless networks. Finally, we give a suggestion on how to tradeoff between the quality of speech and the maximum number of voice calls in Wireless LANs Key Words WLAN, VoIP, IEEE I. INTRODUCTION Voice over IP has potentially been becoming to be a low-cost alternative to Public Switched Telephone Network (PSTN) because of the rapid advances of network technologies and the cost-saving incentive for both individual users and service providers. Since VoIP service requires the real-time delivery of packetized voice traffic across the best-effort IP-based networks, a great demand on studies for real-time guaranteed voice transmission has emerged and thus grows into a very important issue for modern telecommunications systems [1]. In PSTN, bandwidth is dedicated for each voice call session and thus the delay incurred in voice conversation is minimal. However, in contrast to PSTN, IP networks offer no any guarantees of bandwidth allocated and delay bounded for any voice call because most IP networks do not distinguish time-sensitive voice data from usual data traffic. Both types of data packets mixed in the same network infrastructure have to compete for the whole bandwidth affordable in the scenarios of wired network connected with a last hop wireless link. Owing to the best-effort nature of IP networks and the high error rate of wireless link, most voice IP packets may suffer many impairments of transmission, such as packet loss, delay and jitter. Providing VoIP services with satisfied speech quality in wireless Internet is more difficult than in wired network due to its high bit error rate (BER) of wireless link. In wired networks, VoIP transmission impairments are generally caused by network congestion; however, in wireless networks they can be caused by the degradation of the signal strength (due to interference or collision) and congestion. In addition to high BER, the best effort service of IEEE provides voice packets without any guarantee of bounded conversation delay and may be dropped finally by the VoIP receivers within the network. In this study, we analyze VoIP performance in the environment of Internet with IEEE wireless access networks, in which the access points (APs) support both usual non-voip and VoIP data packets. The performance is measured in terms of the number of simultaneous VoIP calls that a single AP running DCF mode can support in the environment. In our experiment, wireless VoIP system is considered in a last-hop scenario. Voice streams have to traverse wired networks before they reach the AP, which is the conjunction point of a wired network and the wireless channel. II. PACKETIZATION AND VOICE CODERS The human voice is initially digitized into a bit stream by an analog/digital (A/D) converter and then followed by a series of compression process before transmitting or storing. The bitstream of voice data are usually kept in constant bit rate and need to be packetized into IP packets when entering into the IP networks for transmission. Voice signals packetized to audio packets by encoding procedure are transported in IP networks via RTP protocol. Therefore, each voice packet incurs an uncompressed 40-byte header that is comprised of 20 bytes for the IP header, 8 bytes for the UDP header, and 12 bytes for the RTP header. Voice Codec are designed mostly according to ITU-T standards, such as G.711 [2], G [3], G.729A [4], and ilbc [5] voice coders. In these standards, documents are developed to specify how segments of analog voice signals are to be encoded into digital data streams and the associated packetization process. Each standard bears specific requirement of transmission rate for various voice applications. G.711 coder s transmission rate is 64 kbps, consisting of 8 khz sampling of 8 bit signals. Coder G723.1 is based on MP-MLQ technology with two transmission rates i.e., 5.3 and 6.3kbps. The G.729A voice coder uses CS-ACELP coding technique and produces a speech rate of 8 kbps. ilbc coder is designed for narrow band speech, with a sampling rate of 8 khz. The ilbc codec, which is similar to G.723.1, also supports two speech rates, i.e., 13.3 and 15.2kbps. Detailed Information about four modern codecs is shown in Table 1..

2 Table.1 Characteristics of Different Voice Coder Codec G.711 G G.729/A ilbc Encoding technique PCM MP-MLQ / ACELP CS-ACELP FB-LPC Coding speed (Kbps) / / 15.2 Frame size / 20 Processing delay (ms) Unknown Look ahead delay (ms) Unknown Payload / / 38 III. VOICE QUALITY IMPAIRMENT AND METHODS In this section, we first describe the two basic factors: latency and packet loss, which would affect call quality and QoS (quality of service) of VoIP in wired as well as in wireless network. In addition, as that we mentioned above, the speech quality assessment methods the Mean Opinion Score (MOS) [6] and E-Model [7] would be introduced later. A. Delay and Packet Loss The time elapsed before a packet arrives at its destination from the sending station is called transmission latency or delay. Generally, it is accepted for toll quality phone calls that the end-to-end latency should be less than 150 ms. According to ITU recommendation G.114 [8], longer end-to-end delays between two conversation parties, e.g., greater than 150 ms, would make conversation uncomfortable (as shown in Table 2). While end-to-end latency should include the buffering and processing time experienced in network nodes, in this study, we consider end-to-end delay only as the transmission time because the simulator NS2 does not support the trace of processing and buffer delay. Packet loss in the wireless network occurs frequently and therefore is referred to as the most serious problem that voice transmission over the wireless LAN encounters. The reasons why packets are lost in a wireless network are mainly due to the heave traffic contention in the CSMA domain such that most packets would be discarded during congestion time. Human perception of voice received can generally put up with about 1-3% of lost packets. Some voice coders degrade even more severely because they compress the data more rigorously. In this experiment, we assume that people can afford at most 3% of loss for most voice coders. VoIP connection can be thought of failure if the rate of packet loss is greater than 3%. B. Speech Quality Measurement Speech quality measurement can be carried out using either subjective or objective methods. In our experiment, we would adopt one subjective method and one nonintrusive method to evaluate the call quality over wireless network. Mean Opinion Score (MOS) is the most widely used subjective measure of voice quality and is recommended by the ITU-T. It scores voice quality ranging from level 1 (represents for unacceptable) to level 5 (stands for excellent). The objective method, such as the E-Model [9], defined in the ITU-T Rec. G.107, is a computational tool to predict the subjective quality of a telephone call based on its characteristic transmission parameters. It combines the impairments caused by these transmission parameters into a rating R, which ranges between 0 and 100 and can be used to predict subjective user reactions (e.g. the MOS). The R-factor is related to the MOS through the following set of expressions: MOS = 1 MOS = 4.5 MOS = R For R < 0 For R > R( R 60)(100 R) For 0 < R < 100 (1) Table 2 ITU recommendation of end-to-end delay times Total one-way delay Recommendation for use Under 150 ms Acceptable ms Acceptable for some application Above 400 ms Unacceptable for general networking planning ITU-T defines R-factor that combines different aspects of voice quality impairments: R = Ro Is Ie Id +A (2) where Ro represents signal-to-noise ratio; Is includes the effects of impairments that occur simultaneously with the voice signal; Ie is an equipment impairment factor associated the losses; Id represents the impairment by the mouth-to-ear delay of the path; A is the expectation factor that callers are willing to tolerate because of the access advantage ; for example, the advantage factor of mobile telephony is assumed to be 10. Since no agreement has been reached for the case of VoIP services, we do not consider the A- factor in this study. According to the default value defined in ITU-T Rec. G.107, we shorten the expression for the R-factor to Equation (3) R = 94.2 Ie Id Id = 0.024d d (d 177.3) H (d 177.3) (3) Ie = ln (1+ 3 e) where d is the one-way delay and H represents Heavyside function. e represents the total loss probability and γ 1 is a constant that determines voice quality impairment caused by encoding, and γ 2 andγ 3 describe the impact of loss on perceived voice quality for a given codec, as shown in Table 3 [10]. According to Equation (3) and Table 4, we can get the R-factor for G.711: R = d 0.11d (d 177.3) H (d 177.3) 1 2 ln (1+ 3 e) (4) After R-value is calculated, then we can convert the R- value into the corresponding MOS value by equation (1). According to G.107 Recommendation, if R-value is over 70, the speech quality generally is accepted by most users. In the other words, quite a few users satisfy speech

3 quality with the MOS value over 3.6. Before we get R- value or MOS value, we must obtain related impairment factor, such as the delay time and packet loss rate for different codecs. Table 3: The values of 1, 2 and 3 Codec γ 1 γ 2 γ 3 G G G VI. SIMULATION MODEL AND ASSUMPTIONS In this section, we conduct several simulation experiments to obtain the basic evaluations. We perform the experiments on the Network Simulator NS2 for all scenarios considered in the paper. A. Wired-cum-Wireless Scenario. In our experiment, we build a simulation scenario: wired-cum-wireless scenario. Each wireless station can directly communicate with the AP with one hop apart. Also, we assume that wireless stations and the AP operate at a data rate of 11 Mb/s. The Wired-cum- Wireless scenario is illustrated in Figure 1, in which the channel between Router 1 and Router 2 is seen as a Wide Area Network (WAN), providing the WLAN access to the wired networks. W W 2Mb/s 10ms R1 100Mb/s 5ms Fig. 1 Wired-cum-Wireless scenarios B. Traffic Model There are two different traffic models in use for our simulations, one for ftp traffic over TCP/IP called data model and one for VoIP traffic over UDP/IP called voice model. Each station involving with a voice session generates and receives only voice traffic. In the WLAN, only VoIP connections are established for all the mobile stations. In this study, we set the receiver window size to 10, which is determined by performing a experimental sniffing our Microsoft OS environment and averaging the measured window sizes. This differs from the size of 42 packets claimed in common. Intuitively, we can think voice traffic as that generated by a two-state process. In other words, some user A alternates between periods of talk-spurts (ON) and silence periods (OFF). We assume that the average ON time is 352ms and the average OFF time is 650ms.. In this study, we will increase the number of VoIP from 1 with a fixed TCP flow linearly. C. Error Model A two-state Gilbert Model is used to simulate the packet loss. The Gilbert Model is well-known to representing the packet loss behavior of a real network. It is a two-state time-continuous Markov chain as shown in R2 100Mb/s 5ms LAN WAN LAN Wireless LAN AP M M Figure 2, in which the two-state set s = {Good, Bad} and Markov chain is entirely defined by the two parameters: q is the probability that the next packet is lost, providing the previous one has arrived and p is the opposite. In our experiment, the selected BER values for Good and Bad states are 10-6 and 10-2, respectively. We choose medium packet loss with parameters q = 0.1 and p = 0.3 [11]. 1-q Good q Bad p BER G = 10-6 BER B = 10-2 Fig. 2 Error model of wireless channel 1-p V. RESULTS AND ANALYSIS OF SIMULATION Since the packet loss and the mean one-way delay are measured to assess the quality of speech, for this simulation study, we consider two cases by these two metrics: How delay of VoIP affected by the number of non-voice flows is reported in Case 1. Case 2 presents the variations of packet loss rate with the increase of VoIP and non-voice data flows. In addition, relationship between MOS score and VoIP calls will be depicted later in the following Case 2. A. Case 1 Variation of delay with increasing VoIP calls in the presence of Non-VoIP flows In this study, we pay our attention on the difference between downlink and uplink delays and found that uplink delay of VoIP is always fluctuating between 20ms and 25ms and not susceptible to variation within increasing number of non-voip flows. We observe the difference between downlink delay and uplink delay. In this experiment, uplink delay of VoIP can always be seen between 20ms and 25ms and not susceptible to variation within increasing number of non-voip flows. Under DCF media access mechanism, the AP must competes with other mobile nodes over only one shared channel. According to this view, it s reasonable that longer delay will be experienced for the downlink transmission and contributes to depredate the VoIP performance. Based on this viewpoint, we observe only downlink delay with effects on non-voip connections. Fig. 3 shows the relationship of mean delay versus the number of VoIP connection for codec G.711. By the experiments, the maximum number of voice calls can be determined under the conditions for different number of TCP flows from 1 to 7. The mean delay increases rapidly with more TCP flows no matter which coder we select. Fig. 3 illustrates that the capacity of IEEE for VoIP flows in the presence of one TCP connection is 16, which is the lowest among the four voice codecs. Fig. 4 shows the capacity of voice call for G It is obvious that packet with more payload size will result in more delay. Another reason responsible for high delay is encoding rate which occupies and reserves more bandwidth. For these codecs, only the delay for G in the presence of 7 TCP flows is below 150ms. But it is not sure whether G provides the best quality of speech

4 or not. According to E-model, G is extremely sensitive to packet loss and its R-factor is smaller than other codecs under the same network condition. In lowbandwidth network, we can assure that packet with smaller size and lower rate has less delay and the maximum capacity of VoIP connections. In other words, we can assume that when network s bandwidth is large, such as g wireless network, can reduce delay and decrease the difference among the four codecs. active nodes. In this experiment, the majority of packet loss comes from collisions between AP and mobile nodes. In Fig. 6, we see that the capacity of IEEE for VoIP in the presence of one TCP flow for coder G reduces to 26 and 21 for G.729. In addition, we also observe that the shape of curve for G.711 with five TCP flows is steeper than other codecs. It is convinced that high loading network increases packet loss dramatically, especially coder G.711. Mean Delay (Sec) Fig. 3 Mean delay v.s. number of VoIP for codec G.711 Mean Delay (Sec) Probability of Packet Loss Fig. 5 Packet loss v.s. number of VoIP for codec G.711 Probability of Packet Loss Fig. 4 Mean Delay v.s. Number of VoIP for codec G From the above results, it is clear that the number of TCP flows has quite great influence on delay time, especially G.711 coder. However, it is not evident enough to determine the quality of speech, so it is necessary for us to consider another important factor packet loss to determine whether the quality of voice can be satisfactory for most users. B. Case 2 Variation of packet loss with increasing VoIP in the presence of Non-VoIP flows Figs. 5 and 6 show the relation between packet loss and the number of VoIP connections for different codecs. Although coder G.711 has large size of payload, the variation of its packet loss curve is similar to other codecs in the presence of 5 and 7 TCP flows. Only G.711 and ilbc, their probability of packet loss are below 3%. We observe that the larger number of VoIP connections is, the more packet loss is measured. Under this case, the number of users in wireless network dominates whether the probability of packet loss is high or low. High loss always results from collisions and errors which signal is interfered with signal generated by other Fig. 6 Packet loss v.s. number of VoIP for codec G C. MOS score with increasing VoIP in the presence of Non-VoIP flows After analyzing effects of network delay and packet loss, we finally present numerical data by MOS score through calculation of E-model. Due to lack of some related E-model parameters (e.g. the Ie values) for ilbc, only MOS score for the other three codecs is depicted. On the basis of the ITU-T Recommendation, the value of MOS below 3.6 can be considered that quality of speech will dissatisfy listeners. Figs. 7 and 8 show the relation between MOS score and the number of VoIP connections for different codecs. We observe all the MOS scores are over 4 in Fig. 7 and are superior to the other two codecs. According to Equation (4) and Table 3, coder G.711 has more advantage than G and G.729 under the same probability of packet loss. By analyzing the E-model s formulas, when one-way delay is over 173.3, delay will gradually dominate the MOS score. It is apparent that the curve of packet loss represents an reciprocal ratio to curve of MOS score.

5 As illustrated by Fig. 8, the capacity of IEEE for G.723.1VoIP decreases to 20 in the presence of one TCP flows. Although coder G has the maximum capacity in terms of measured delay, packet loss leads it to getting poorer quality with the increase number of voice calls. There is a tradeoff between quality of speech and maximum number of voice calls. If we choose G.711 as our VoIP coder, we would get excellent quality of speech, but quality of speech and maximum capacity will degrade rapidly in a heavy-loading network. In contrast, coder G.723.1, it costs just a little quality of speech to raise the maximum capacity. Nowadays, it will be better to select ilbc or G.729 to avoid the drawbacks of G.711 and G Finally, we obtain the maximum capacity for different coders on account of MOS value. It can be observed that the curve of maximum call for coder G is similar to that for coder ilbc, but it is still superior to coder G.711. From what has been discussed above and result from Fig. 9, it seems reasonable to conclude that coder G.729 has the maximum voice calls on the basis of MOS score under the same network condition. IV CONCLUSIONS In this paper, we have discussed the capacity of networks for voice and observed the maximum number of connections that a single AP can support for each voice codec. We have shown that capacity of wireless network for VoIP is highly sensitive to the delay and packet loss for series of codecs. As we discussed early in the paper, the use of G.729 and ilbc codecs has been shown to allow greater capacity than the use of G.711. Meanwhile, it is sure that the use of ilbc showed better quality of speech than the use of G MOS Score MOS Score Fig. 7 MOS score v.s. number of VoIP for codec G.711 Fig. 8 MOS score v.s. number of VoIP for codec G Number of TCP Connections Fig. 9 Number of TCP v.s. number of VoIP connections Coder G.711 is highly sensitive to one-way delay in the presence of multiple non-voice flows. If we want to obtain better voice quality, it is essential to decrease the number of TCP flows or increase bandwidth of channel. As a whole, to overcome the problem of packet loss over wireless channel is much more difficult than that of delay. The way to solve high one-way delay can be practiced by enhancing the priority of voice or raise network bandwidth. Only by developing effective algorithms and methods to reduce packet loss and error can help us to improve quality of speech, especially in lossy wireless network REFERENCES [1] J. Wang, P. J. McCann, P. B. Gorrepati, and C. Liu, Wireless Voice-over-IP Implications for Third-Generation Network Designed, Bell Labs Technical Journal, [2] ITU-T Recommendation G.711, Pulse Code Modulation (PCM) of voice frequencies, [3] ITU-T Recommendation G.723.1, Dual Ra Speech Coder for Multimedia Communications Transmitting at 5.3 and 6.3 kbit/s, [4] ITU-T Recommendation G.729, Coding of speech at 8 kbit/s using conjugate-structure algebraic-code excited linear-prediction (CS-ACELP), [5] S. Andersen and A. Duric, Internet Low Bit Rate Codec (ilbc), in Proc. IETF RFC 3951, [6] ITU-T Recommendation P.800, Methods for Subjective Determination of Transmission Quality, [7] ITU-T Recommendation G.107, The E-Model, A computational model for use in transmission planning, [8] ITU-T Recommendation G.114, One-way Transmission Time, [9] ITU-T Recommendation P.861, Objective quality measurement of telephone-band ( Hz) speech codecs, [10] ITU-T Recommendation G.113, Provisional planning values for equipment impairment factor Ie, [11] J. Richiardi and J. Fierrez-Aguilar, On-line Signature Verification Resilience to Packet Loss in IP Networks, in Proc. 2nd COST-275 Workshop on Biometrics on the Internet, COST275, pp , Vigo, Spain, March 2004.