Downlink Optimization of Indoor Wireless Networks Using Multiple Antenna Systems Bongyong Song, Rene L. Cruz and Bhaskar D. Rao Department of Electrical and Computer Engineering University of California, San Diego, La Jolla, CA 92023-0407 Abstract - We compare the performance of two multiple antenna systems to be used in quality of service (QoS) supported indoor wireless networks. While a conventional array antenna system (AAS) has collocated, closely spaced antenna elements, a distributed antenna system (DAS) has largely spaced antennas over the entire area of radio coverage. To support multimedia applications requiring high bandwidth and on time delivery, we propose a set of highly spectrum efficient radio resource management algorithms. We focus on the optimization of downlink since many kinds of Internet traffic show the downlink dominance in their traffic asymmetry. To maximize the downlink throughput, we present a new transmit beamforming algorithm which can be equally applied to both DAS and AAS. The beamforming algorithm is integrated with a link scheduling algorithm that exploits the space division multiplexing (SDM) capability of multiple antenna systems to meet the QoS requirements of all terminals. Numerical examples conducted for a line of sight (LOS) environment demonstrate that a network with DAS outperforms one with AAS in terms of signal coverage and provides 40 - 160% higher capacity. Index Terms - Multiple Antenna Systems, Beam- forming, Power Control, Link Scheduling, Duality I. I NTRODUCTION With the recent dramatic growth in wireless communi- cations together with the Internet, technologies in wire- less communications and networking are being advanced with the goal of delivering multimedia applications and services, at anytime, anywhere and on any devices. This rapid growth of the untethered multimedia demand facilitates the migration of current wireless networks into broadband networks. Since many kinds of Internet traffic This research was supported in part by the National Science Foundation Grant No. ANI-0123421. show the downlink dominance in their traffic asymmetry, maximizing downlink capacity is particularly important. CDMA/HDR [1] is designed to provide the downlink capacity of up to 2.4Mbps and high speed downlink packet access (HSDPA) mode of UMTS aims at over 10Mbps downlink capacity. The latest wireless local area network (WLAN) standards (802.11a/g and HIPER- LAN/2) support up to 54Mbps. High demand for capacity can be handled by various techniques in communication systems. Utilizing multiple antennas is one of the most promising physical layer approaches to increasing system capacity. A conventional array antenna system (AAS) has an array of antenna elements closely spaced altogether and an array pro- cessor computes a beam pattern that increases signal power and reduces interference at the receiver. Due to the interference suppression capability of an array, space division multiplexing (SDM) in downlink and space division multiple access (SDMA) in uplink are attain- able. Beamforming at a transmitter is in general more difficult than beamforming at a receiver since a transmit beamforming affects the performance of all receivers via interference whereas beamforming at a receiver can be executed independently. However, higher capacity demand for downlink necessitates more efficient transmit beamforming at an access point or a base station. The zero-forcing approach proposed by Gerlach and Paulraj [2] maximized the individual SNRs while placing nulls to all directions causing interference. Although compu- tationally efficient, zero-forcing can result in reduced signal power at the receiver and, limits the order of SDM to the number of antenna elements. Rashid-Farrokhi, et al. [3] found an iterative joint beamforming and power control solution for reaching specified SINR levels at each receiver with the minimum total transmit power for arbitrary number of users. Another iterative algorithm developed by Montalbano and Slock [4] finds a solution that maximizes the minimum signal to interference ratio (SIR) of all users. The convergence of the algorithm is provided in [5]. Recently, Koutsopoulos, et al. [6], proposed a set of iterative heuristics attempting to am- 0-7803-8356-7/04/$20.00 (C) 2004 IEEE IEEE INFOCOM 2004