Multimedia Communications over Wireless LANs via the SWL Protocol

Transcription

1 Multimedia Communications over Wireless LANs via the SWL Protocol Garret Okamoto and Guanghan Xu Department of Electrical and Computer Engineering The University of Texas at Austin Abstract The transmission of multimedia data over networks has increased steadily over the past few years and this increase is projected to accelerate in the future. However, virtually all current products and research for multimedia traffic over networks have concentrated solely on transmission of multimedia applications to and from wired terminals. Excluding mobile terminals from multimedia applications such as voice clearly limits the flexibility and potential of those applications. Additionally, the bandwidth allocated for wireless LANs in the IEEE standard is limited and overall throughput is limited, and these limitations will become a bottleneck for expanding wireless network capabilities. In this paper, we exploit another resource, i.e., space, and design a new Smart Wireless LAN (SWL) protocol to achieve throughput multiplication and flexibility for mixed traffic networks. Experimental studies and computer simulations will show the feasibility and performance benefits for using SWL with wireless LANs, particularly for multimedia applications. 1. Introduction The IEEE wireless data standard [1], [2], [3] was created to standardize wireless Local Area Network (LAN) systems to make the systems practical and affordable. It was designed to serve as the wireless version of the IEEE 82.3 standard, commonly known as Ethernet. In the standard, the base station serves as an access point, bridging traffic between mobile stations and the wired network. The base station grants each node a time slot in an orderly, sequential manner. At the end of each access cycle, a contention period allows a node entering the area to announce itself or for terminals to communicate directly with each other. Since the transfer rates in the standard are set at 1 or 2 Mbits/s, this sequential operation will place a clear limitation on having many terminals use data and multimedia services. Additionally, the standard does not include priority designations for data, which makes it virtually impossible to guarantee the quality of service needed by multimedia transmissions. In this paper, we utilize SDMA (Space-Division- Multiple-Access) and the efficient scheduling scheme for wireline networks presented in [4], [5] and propose a new SWL (previously known as the Spread Spectrum and Space-Division-Multiple-Access, or SS-SDMA) protocol for wireless LANs to achieve throughput multiplication and significant reduction of communication delays. The feasibility of a similar SDMA/TDMA (Time-Division- Multiple-Access) scheme for wireless LANs was demonstrated in [6]. We propose to achieve throughput multiplication by exploiting the rich spatial diversity existing among spatially separated terminals. Spatial diversity is demonstrated by the amplitude and phase pattern of the data vectors received by an antenna array. Each transmitter located at a certain place has its unique pattern, also called a spatial signature. Once the spatial signatures are acquired, different co-channel signals can be separated based on their unique spatial signatures. Therefore, we can increase the number of virtual time slots by allowing different terminals to transmit in the same time slots without significantly interfering with each other. The SS-SDMA protocol [7] was renamed the Smart Wireless LAN protocol after several fundamental changes were made to improve the performance of the physical layer system and to fully comply with the protocol. For example, the uplink and downlink algorithms were modified (as described later), only one user is now allowed to transmit at a time during the contention period (required for compatibility and to obtain spatial signatures, as described later), and a bitwise XOR encryption scheme is used instead of the public key encryption algorithm that was used previously. This new protocol has additional features such as simple implementation, adaptability to multimedia traffic with diverse bandwidth requests, network security, guaranteed fairness in bandwidth sharing, and ease of adaptation to the wireless LAN standard. Also, this protocol adds priority level designations to the

2 packets to allow for delay-sensitive communication links for multimedia applications such as voice or video. A combination of throughput performance evaluations, computer simulations, and RF experimental studies demonstrate the feasibility and benefits of the SWL protocol. The only new requirements of this protocol are an antenna array installed at a base station and advanced signal processing software to process the received data. 2. SDMA Background A diagram of a six-element uniform linear antenna array with two impinging wavefronts is shown in Figure 1. The antenna elements are spaced a uniform distance apart, typically 1/2 of the transmission wavelength. Figure 1 and the following discussion pertains to the uplink case of multiple (d) wireless terminals transmitting to a base station. s 1 (t) θ 1 θ2 s 2 (t) x 1 (t) x 2 (t) x 3 (t) x 4 (t) x 5 (t) x 6 (t) Figure 1. Uniform Linear Array Example To develop the equations for our model, first let us consider the signal received at one of the antenna elements from a single source, r(t) = s(t)e jwt, where s(t) is the complex envelope of the transmitted baseband signal and w is the carrier center frequency. The complex envelope s(t) can be represented as s(t) = d n p(t-nt b ) (1) n where d n is the sequence of complex data symbols, p(t) is a real pulse, and T b is the pulse duration. Let us assume for now that we only have a direct path signal and no multipath components. The received signal x(t) at an antenna element with respect to the reference signal r(t) is then x(t) = r(t-τ) = s(t-τ)e jw(t-τ) (2) where τ = sin(θ)/c is the propagation delay between the reference and the antenna element, and c is the speed of light. For SWL and IEEE 82.11, the signal has a maximum bandwidth of about 1 MHz, which is much smaller than its carrier frequency, i.e., 9 MHz or 2.4 GHz. Therefore, the narrowband signal model applies here, and s(t-τ) s(t). Demodulating and substituting the narrowband signal envelope yields x(t) = s(t) e jw(t-τ). A snapshot vector model of the received signal due to one incident source in the presence of noise n(t) can then be represented as x(t) = a(θ)s(t) + n(t) (3) a(θ) = [e -jwτ(1) e -jwτ(2)... e -jwτ(m) ] (4) where τ(1) τ(m) are the propagation delays between the reference and the first to m th antenna element. If we assume that we have N total signal components, consisting of a direct path signal and N-1 multipath components, our received signal is N x(t) = a(θ 1 )s 1 (t) + α n a(θ n )s 1 (t-τ n ) (5) n=2 where the first component is assumed to be the direct path component, α n is the phase and amplitude difference between the n th multipath and the direct path, and θ n is the angle of arrival of the n th multipath component. Note that the multipath components will have different delays, depending on their angle of arrival. Since wireless LAN signals are transmitted in a short range local communication environment, the time delays of their significant multipath components, {τ n }, are typically smaller than the chip duration of the signal, which is roughly 1 ns [8], [9]. Hence, s(t-τ) s(t) is typically true for the multipath components in addition to the direct path component (which was shown earlier). Our received signal can now be expressed as N x(t) = a(θ 1 )s 1 (t) + α n a(θ n )s 1 (t) = a 1 s 1 (t) (6) n=2 where a 1 is the spatial signature associated with terminal 1. If we now assume that we have d terminals transmitting at the same time, our received signal is d x(t) = a k s k (t) (7) k=1 where a k is the spatial signature associated with terminal k and s k (t) is the complex envelope of the transmitted baseband signal from terminal k. Written in vector form, the received signal is x(t) = As(t) + n(t) (8)

3 where A = [a 1, a 2,, a d ] denotes the array response matrix, with columns associated with the spatial signature of each transmitted signal. 3. The Smart Wireless LAN Algorithm Each Time-Space frame is divided into two periods, the contention period and the contention free (data) period. When a node wishes to join a network, it issues a request for authentication (RFA) during the contention period. The RFA includes the type of transmission and the data length (for data transfers) or timing requirements (for voice, video). If the RFA is successful, the base station responds by sending out a block of random text to the potential user's node. The user encrypts the text string using the user's password as a cipher key. If the network gets the proper encrypted string of data back, the node is authorized for network access and will be allocated a time slot (or slots, if more than one slot per frame is requested) during the data period for its transmission. The RFA can only succeed during the contention period if its request satisfies the Distributed Coordination Function (DCF) criterion. In the DCF, if more than one request is sent in a contention period slot, then all requests in that slot are assumed to fail. Note that this criterion is conservative because, due to the capture effect [1], it may be possible for a particular contention request to succeed even though the number of requests during that time slot exceeds the maximum allowable number. This is because the loss due to fading and propagation over radio channels fluctuates the received power of transmitted signals, so a base station might still receive one packet with the maximum received power correctly, even if two or more packets happen to collide. The length of the contention period is adaptively selected, subject to maximum and minimum parameters set by the network. Each slot that has a contention failure increases the length of the contention period by one, each slot that has no contention requests reduces the contention period by one, and the length is unchanged if the contention is successful. The contention period is also reduced when the network is operating in an overloaded state, as described later. An example of a Time-Space SWL frame is shown in Figure 2. There are a total of N time slots in each frame, with the number of time slots in the contention and data periods (N c and N r, respectively) adaptively adjusted as explained above depending on the input traffic conditions. There are N s (four) rows in the contention free period because the use of SDMA allows for four users to transmit at once while there is only one row in the simulation. Note that the SWL simulation assumes an eight-element uniform linear antenna array at the base station to separate the four transmissions in the same frequency band at the same time. The shaded slots represent terminals (1-7) transmitting the high-priority voice data. The other numbered slots represent terminals (8-19) that are transmitting messages or performing file transfers. The slots with no numbers in them are time slots that have not been assigned to any terminal. Terminals 4, 6, and 17 have successful RFA requests to join the network and will probably use those time slots in the next frame. In fact, those terminals may even push the network into a low-overload situation, as discussed below. Ns Nr High Priority Terminals N Contention Free Slots Figure 2. SWL frame structure Nc Contention Slots Low Priority Terminals The global scheduler operation can be summarized as follows. First, all high priority data requests are satisfied before any low priority data request is considered. If the high priority data requests cannot be satisfied in one frame, the requests are served in a round-robin fashion. Second, if there are remaining data slots, they are shared in a round-robin fashion by the low priority requests. Third, when the network is operating in high-overload (the high priority data requests cannot be satisfied in one frame) or low-overload (the low priority data requests cannot be satisfied in one frame) modes, the network increases the length of the data period, which reduces the length of the contention period. This has the beneficial effects of both increasing the number of time slots available in the data period where they are needed by the overloaded network and reducing the probability that new data requests will succeed in the contention period and further overload the network. Finally, one segment of the data period is reserved for the base station, which uses it to broadcast to all users and potential users the length of the contention period and the time slots allocated to each user for the next data period. Other segments can be reserved by the base station to handle administrative or bookkeeping tasks.

4 This protocol mirrors the protocol as closely as possible and mobile terminal operation would not need to be changed. However, this new protocol has the following major features: 1) multiple uplinks and downlinks can be carried out in the same time slot and same frequency band; 2) the transmission of active terminals with different bandwidth is organized by using a global scheduler to achieve fair delay performance; and 3) priority designations allow the network to meet guaranteed maximum delay requirements needed for delaysensitive multimedia applications such as voice links. 4. Smart Wireless LAN Physical Layer A simplified block diagram of the physical layer for the SWL system is shown in Figure 3. This structure was created to be compliant while allowing for the use of SDMA and was simulated using Matlab. Data is randomly generated for four users, with three of the users serving as interference sources. Encryption is an optional feature that is performed using the wired equivalent privacy (WEP) algorithm used in (bitwise XOR with a pseudo random key sequence created by a user's secret key). The data is modulated with BPSK (binary phase-shift keying) or QPSK (quadrature phase-shift keying) to achieve the 1 and 2 Mbits/s data rates specified in Each user uses the same code to spread their data, an 11-chip Barker code. The channel model is randomly generated each time the simulation is run and can vary significantly from simulation to simulation. Additive noise is scaled to achieve the specified SNR (signal-to-noise ratio) between the desired signal and the gaussian noise. The interleave and deinterleave operations are an optional feature of the SWL system which is being studied to see if interleaving improves the quality of the transmissions. The reason that interleaving has potential is because bit errors due to propagation, especially in indoor environments, tend to occur in bursts. These bursts are not recoverable by the Viterbi decoding; however, if we spread these errors out by interleaving the data we can potentially recover from the burst errors. Multiple users transmitting in the same frequency band at the same time requires special care for the uplink and downlink of signals. When the base station wishes to downlink data to four terminals at once, it extends the above block diagram in the following manner. First, it creates the data vectors for all four terminals and uses the assumed knowledge of their spatial signatures to perform beamforming to mitigate interference between the terminals. Second, it inserts a 3-chip delay between each of the resulting signal vectors, as shown in Figure 4. Each row in Figure 4 represents the spreading code used by a terminal and the actual starting point of the Barker code is shown by a solid vertical line. Because of the ideal property of the Barker code (minimal correlation between the various parts of the code), this allows the coding gain from spreading to be achieved despite all four users using the same code. Due to the beamforming effectiveness as shown in [11], each user receives one significant and distinct signal to synchronize to and can easily despread its signal in the standard manner. Beamforming techniques currently being studied include randomly generated spatial signatures, placing nulls for the other users, and optimal beamforming methods. Data Creation Channel Effects Additive Noise Compute BER Interference Convolutional Code Data Pulse Shape Raised Cos Despread Signal Viterbi Decoder Encrypt Data Spreading via Barker Code Demodulate Signal Resolve Phase Ambiguity Interleave Data Modulation BPSK/QPSK Deinterleave Data Decrypt Data Figure 3. SWL physical layer block diagram Figure 4. Implementation of the chip offset to enable multiple user downlink When four users wish to uplink to the base station at the same time, the base station can separate the signals because it already knows the spatial signatures of the individual users. Using that knowledge, the base station performs pseudoinverse beamforming to obtain the matrix that will be multiplied with the received waveform to obtain the four data vectors containing the signals of the four terminals. In pseudoinverse beamforming, the weight vector w can be found by w = arg min X - Aw H X 2 (9) w where X is the received signal. The least squares solution w H = (A H A) -1 A=A # is designed so that the weight vector

5 w i a k for i k and a H i w i =1. In effect, the weighting routine steers the beam in the direction associated with the array response vector of the i th source and places nulls in the other source directions to minimize their interference. A maximum likelihood method is also being studied which should achieve superior performance than the pseudoinverse method at a cost of additional computational complexity. The assumption that we already know the spatial signatures of each terminal is a reasonable one because each terminal is required to transmit a frame to the base station during the contention period in order to join a network. Since only one user is allowed to transmit at a time during this period (adhering to the Distributed Coordination Function Protocol in 82.11), we can easily find that user's spatial signature. Experimental studies discussed in the next section show that the spatial signature remains fairly constant over time for a stationary terminal. If the transmission quality from a terminal appears to be degrading, the base station can send a request to that terminal to transmit again during the contention period to update its spatial signature. 5. Experimental Results In order to ascertain the feasibility of the SDMA scheme in wireless LAN environments, a uniform linear antenna array of five elements with separation 1 cm and carrier 1.7 GHz was built and experimental studies were conducted of some typical scenarios at our laboratory facility in the J. J. Pickle Research Campus. The antenna array was placed near the ceiling of the lab at a height of around 3 m. A single transmitter was used and it was placed at 5 locations, where it transmitted QPSK signals with a center frequency of 8 khz. The transmitter locations 1-25 were placed at a height of 1.3 m and locations 26-5 were placed at a height of 1 m. Figure 5 shows the environment where the experiments were conducted. The antenna array position was fixed and it collected the data transmitted by the transmitter at each of the locations shown. First, we studied the stability of spatial signatures for stationary transmitters to discover how fast we need to update each spatial signature. Figure 6 shows the changes in the spatial signature within 1 minute for a stationary transmitter when there were 6 people walking around the antenna array and the transmitter. From the figure, it is easy to see that the spatial signature does not vary significantly within 1 minute, and definitely does not within 1 seconds. Measuring changes in the spatial signature for a stationary transmitter without the people walking around the antenna array and the transmitter produced similar but slightly better results, as expected. (m) Locations of the Antenna Array and 5 Wireless Terminals (m) 8 Antenna Array 5 Figure 5. Location of the antenna array and 5 wireless terminals for spatial signature experiments Percentage of change Time [1s] Figure 6. Spatial signature variation Another issue we studied was how the spatial signatures differ for closely spaced transmitters. If the spatial diversity between two terminals is too small and they are assigned to the same time slot, then the base station may not be able to separate them. As shown in Figure 5, there were quite a few closely spaced transmitter pairs (ranging from 1 to 5 cm apart), e.g., (1,36), (5,6), etc. in our experiment. The correlation of their spatial signatures is shown in Table 1, from which it is easily seen that most closely spaced pairs have significantly different spatial signatures. Therefore, due to a large amount of short-delay multipath in an indoor environment, a little spatial separation usually means significant spatial diversity. From the correlation of all

6 possible pairs, we found that there were only 61 pairs out of 5*49/2 = 1225 with a correlation larger than.9, so the chance of selecting these pairs is only about.5. The base station keeps a record of pairs of terminals with high spatial signature correlation and takes care not to assign them to the same time slots. It should also be noted that our experiment purposely selected transmitter locations that were closely spaced, and a real environment would probably not have numerous terminals just 1 to 5 cm apart. Hence, the spatial signature correlation in a real environment would probably be much less than those in our experiment. Table 1. Spatial signature correlation for closely spaced transmitters Close Pairs 1,35 3,4 2,33 1,48 16,4 23,26 Correlation Close Pairs 1,36 5,6 14,44 13,42 23,24 26,28 Correlation Network Layer Simulation Results The experimental results above were used to select the proper parameters for a computer simulation comparison of the standard with the SWL protocol [12]. A user-specified number of voice, file transfer, and electronic mail ( ) terminals (ranging from 1 terminal to 16 total terminals) submitted requesting packets to contend for access to the network. The requesting packet was transmitted in the contention period using the p-persistent slotted ALOHA protocol on a frame-by-frame basis and contained the terminal ID number, the priority level of the transmission, and the number of slots requested per frame. The voice data was given a high priority designation and file transfer and data were given low priority designations. The parameter p for the ALOHA protocol was set to 1 and.8 for high priority and low priority sessions, respectively. The simulations started with an empty queue and all terminals in the OFF state. The simulations assumed that all transmitted messages reached the base station successfully and thus ignored physical layer effects such as packet loss and the acquisition and updating of spatial signatures that would likely have increased packet delays. The results of the physical layer simulation created to model these effects are presented in Section 7 and the two simulations will be linked in the future to create a comprehensive simulation. The simulations used a time slot size of 5 ms with 4 time slots in each frame. Voice transmissions, after compression and overhead, were assumed to require a transmission rate of 1 kbits/s (one time slot/s). The voice sessions had an average ON period of 1. seconds and an average OFF period of 1.2 seconds. A voice terminal requested one slot per frame. The file transfer sessions had average ON and OFF periods of 1 seconds and 6 seconds, respectively, and the sessions had average ON and OFF periods of 3 ms and 1 ms, respectively. sessions also requested one slot per frame and file transfer sessions requested a random number of slots per frame, uniformly distributed from 1 to 5. A frame in the global scheduler had one row for the (since only one user can transmit at once) and four rows for SWL (since it was assumed that four users could transmit at once) in its contention free period. Each simulation ran for 36, frames. The simulations were run under identical conditions for both the and SWL protocols and the utilization of the network, maximum buffer and queue sizes, maximum delay for high-priority terminals, and a few other output parameters were recorded. Table 2 shows a sampling of the simulation results, displaying for both the and SWL networks the network utilization, maximum delay for voice data (in Time-Space frames), percentage of long (more than 5 frames) delays for voice data, and the maximum buffer size. For example, the last scenario in the table has 35 voice, 1 file transfer, and 35 terminals. The superiority of SWL over for this scenario is shown in every category recorded, with the network utilization of at 82.21% while it was only 18.34% for SWL, and the voice data failures for and SWL contrasting sharply at 23.3% and.14%, respectively. Table and SWL computer simulation results for selected scenarios Protocol Voice File Utilz. Del. >1 sec Buf SWL n/a n/a SWL n/a n/a SWL 5.74 n/a n/a n/a n/a 12 SWL SWL SWL SWL

7 Network utilization was computed by N v ε v γ v + N f ε f γ f + N e ε e γ e (1) N s E[N r ] where N v, N f, and N e are the number of voice, file transfer, and sessions, respectively. The amount of information that a terminal generates when it is active is given by γ v, γ f, and γ e ; the probability that a certain terminal is active is given by ε v, ε f, and ε e ; the number of users allowed to transmit simultaneously during the contention free period is N s ; and the steady state value of the number of contention free slots in each frame is given by E[N r ]. The actual network utilization during the simulations was computed and was found to correspond closely to the theoretical utilization found in (1). The utilization for both SWL and protocols is plotted in Figure 7 for voice terminals and is clearly linear as the number of voice terminals increase, as expected. It is clear from the figure that the utilization of the network is slightly greater than four times the utilization of the SWL network. This result was expected because the SWL network allows four times as many users to transmit at a time. Similar results were found for scenarios with only or file transfer terminals, and for various mixed traffic conditions..25 delays for the network under mixed traffic conditions is shown in Figure 8. It is clear from the plot that the network suffers unacceptably large delay failures as it moves into its moderate and heavily loaded regions. Since it is difficult to see the results for the lightly loaded cases, Figure 9 shows the gradual increase in the percentage delays as the network operates in its lightly loaded region. This figure provides an interesting comparison to the long delays for the SWL network under the same conditions in Figure 1. It seems that the rate of increase in the lightly loaded regions for both networks are comparable. It is interesting to note that the lightly loaded region for SWL appears to be larger than four times that of 82.11, which seems to be due to the nonlinear effect of the adaptive adjustments between the number of time slots in the contention and data periods. Percentage of Voice Delays > 5 Frames Protocol SWL Protocol Number of Terminals Utilization Number of Voice Terminals Figure 7. Voice terminal network utilization A critical requirement of a network with delay-sensitive data is the percentage of delay-sensitive data that suffers long delays in transmission (defined as greater than 5 frames for our simulations). Long delays in voice or video calls could make the data unusable. A plot of the percentage of voice data packets that experienced long Figure 8. Percentage of voice delay failures for for mixed traffic There are a few things that should be mentioned about the simulations. First, note that the same number of terminals transmitting voice, file transfer, and data were used until the number of terminals became greater than 3, then the number of file transfer terminals was set to 1 while the number of voice and data terminals were set equal to each other. The reason for setting a maximum number for the number of file transfer terminals is because the file transfer terminals seemed to have a disproportionate effect on the loading of the network and using more than 1 file transfer terminals obscured the performance effects for the terminals. Note also that the results are fairly good for both cases because of the use of 4 slots/frame and allowing for a delay of 5 frames. Other scenarios have less desirable results for both protocols, but in each case (until the

8 number of users becomes extremely large) the SWL simulation performs well while the simulation can have voice delay failure rates approaching 1 percent. Percentage of Voice Delays > 5 Frames Number of Terminals Figure 9. Percentage of voice delay failures for for mixed traffic, lightly loaded case results, with increasing benefits as the number of multimedia users increase. Both of these results were as predicted from throughput performance evaluations. 7. Physical Layer Simulation Results A computer simulation was constructed via Matlab to simulate the uplink and downlink of the physical layer of the Smart Wireless LAN system. A user-specified number of terminals transmit and/or receive data simultaneously in the methods described in Section 4. Convolutional coding is done as specified in 82.11; however, it and the Viterbi decoding routines were commented out of the program after they were verified to work because they slowed the simulation down. Similarly, the encryption and decryption routines were commented out of the program after they were verified to work. All of these routines will be included later in the simulation after the uplink and downlink algorithms are finalized. 1 2 Percentage of Voice Delays > 5 Frames Number of Terminals Figure 1. Percentage of voice delay failures for SWL for mixed Traffic It is clear from the simulation results that the standard works well for a small number of users, as expected, but becomes rapidly overloaded when too many users attempt to use the network. Hence, the network would refuse a connection or become unstable. Either way, the maximum delay for a user attempting to send multimedia data would become unacceptably long. The SWL results were clearly superior in each case to the Bit Error Rate SNR (db) Figure 11. SNR vs. BER simultaneous downlink transmission to four terminals The simulations used a data frame size of 1 bits, with four users transmitting frames at the same time. Each simulation ran for 1 frames for each random channel, and the average BER (bit error rate) was computed using at least 5 random channels at each SNR level. A typical SNR vs. BER curve is shown in Figure 11, where a 2 db level of beamforming is assumed to have been achieved. Note that the SNR specified does not include the interference in the system due to the other three users which are transmitting at the same time as our desired signal, so the actual SINR (signal-to-interferenceplus-noise ratio) of the system is much worse than the

9 SNR listed in some cases. Also note that the BER results in Figure 11 are for the SWL system without Viterbi decoding. The BER is significantly reduced when Viterbi decoding is included in the simulation, as expected from digital communication theory [13]. The simulation assumed that the base station used an eight-element antenna array while each individual terminal used a single antenna. If we assume that we could have more antenna elements at the base station (which would require a faster DSP processor for real-time processing) or more advanced signal separation techniques (also requiring a faster DSP processor) we can potentially allow for more than four terminals to simultaneously transmit and receive data from the base station in the future. Physical layer simulations analyzing advanced beamforming and spatial signature techniques are currently under development to improve the performance (and demonstrate the potential) of the SWL system. 8. Conclusion The IEEE wireless data standard is being adopted to standardize wireless LAN systems. This system was initially created to handle a few timeinsensitive users at once. An analysis of the standard (confirmed by computer simulations) shows that the network is not adequate for a significant number of users, especially if some of those users desire to use multimedia applications such as voice or video. The SWL protocol exploits the spatial diversity existing among spatially separated terminals to allow multiple users to simultaneously transmit in the same time slots. This advantage allows the SWL system to accommodate a large number of users, including multimedia applications that require real-time transmission. Experimental studies demonstrate the feasibility of using SDMA in a wireless LAN system, with excellent stability in spatial signatures and with low correlation of spatial signatures among even closely spaced terminals. Computer simulation results show that the throughput using SWL is significantly higher than that of and that SWL terminals transmitting multimedia data perform well, clearly demonstrating the feasibility and advantages of the SWL protocol for wireless LAN systems, particularly for multimedia applications. 9. Acknowledgment This work was sponsored in part by the Office of Naval Research under Grant N , the Joint Services Electronics Program under Contract F C-45, National Science Foundation under Grant MIP , Motorola, Inc., Southwestern Bell Technology Resources, Inc., Texas Instruments, and an Engineering Doctoral Fellowship and a Microelectronics and Computer Development Fellowship from the University of Texas at Austin. The United States Government is authorized to reproduce and distribute reprints for governmental purposes notwithstanding any copyright notation hereon. 1. References [1] L. Goldberg, Wireless LANs: Mobile-Computing s Second Wave, Electronic Design, June 1995, pp [2] L. Goldberg, Mac Protocols: The Key to Robust Wireless Systems, Electronic Design, June 1994, pp [3] A. Juodikis, Wireless LANs: Considerations and Implementations, Communication Systems Design, September 1995, pp [4] W. Chen, S.Q. Li, and M. Schwartz, A New Voice Scheduling Scheme for Broadcast Bus Local Area Networks, In Proc. IEEE Infocom 89, 1989, pp [5] S.Q. Li and M. El Zarki, Dynamic Bandwidth Allocation on a Slotted Ring with Integrated Services, IEEE Trans. Communication, July 1988, pp [6] G. Xu and S.Q. Li, Throughput Multiplication of Wireless LANs for Multimedia Services: SDMA Protocol Design, In Proc. Globecom 94, San Francisco, CA, August [7] G. Okamoto and G. Xu, Throughput Multiplication of Wireless LANs: Spread Spectrum with SDMA, In Proc. IEEE VTC 96, Altlanta, GA, April 1996, pp [8] H.L. Bertoni, S. Kim, and W. Honcharenko, Review of In-Building Propagation Phenomena at UHF Frequencies, In Proc. Asilomar 95, Pacific Grove, CA, November 1995, pp [9] W. Honcharenko, H.L. Bertoni, J.L. Dailing, J. Qian, and H.D. Yee, Mechanism governing UHF propagation on single floors in modern office buildings, IEEE Trans. on Vehicular Technology, November 1992, pp [1] K. Sakakibara, Performance Approximation of a Multi- Base Station Slotted ALOHA for Wireless LANs, IEEE Trans. on Vehicular Technology, November 1992, pp [11] W. Lee and S. Pillai, Beamforming for Efficient Interference Suppression in a Mobile Communication Environment, In Proc. Asilomar 95, Pacific Grove, CA, November 1995, pp

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