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Beam Selection Strategies for Orthogonal Random Beamforming in Sparse Networks
"... Abstract—Orthogonal random beamforming (ORB) constitutes a mean to exploit spatial multiplexing and multiuser diversity (MUD) gains in multiantenna broadcast channels. To do so, as many random beamformers as transmit antennas (M) are generated and on each beam the user experiencing the most favor ..."
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Abstract—Orthogonal random beamforming (ORB) constitutes a mean to exploit spatial multiplexing and multiuser diversity (MUD) gains in multiantenna broadcast channels. To do so, as many random beamformers as transmit antennas (M) are generated and on each beam the user experiencing the most favorable channel conditions is scheduled. Whereas for a large number of users the sumrate of ORB exhibits an identical growth rate as that of dirty paper coding, performance in sparse networks (or in networks with an uneven spatial distribution of users) is known to be severely impaired. To circumvent that, in this paper we modify the scheduling process in ORB in order to select a subset out of the M available beams. We propose several beam selection algorithms and assess their performance in terms of sumrate and aggregated throughput (i.e., rate achieved with practical modulation and coding schemes), along with an analysis of their computational complexity. Since ORB schemes require partial channel state information (CSI) to be fed back to the transmitter, we finally investigate the impact of CSI quantization on system performance. More specifically, we prove that most of the MUD can be still exploited with very few quantization bits and we derive a beam selection approach tradingoff system performance vs. feedback channel requirements. Index Terms—Orthogonal Random Beamforming (ORB), beam selection, sparse networks, opportunistic scheduling, Multiuser Diversity (MUD), broadcast channel, feedback quantization. I.
Uplink Scheduling in OFDMA Systems using Opportunistic Beamforming
, 2010
"... Uplink scheduling in OFDMA systems using ..."
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Opportunistic Interference Management: A New Approach for MultiAntenna Downlink Cellular Networks
, 2016
"... approach for multiantenna downlink cellular networks ..."
Adaptive Beamforming with PerAntenna Feedback for MultiCell Cooperative Networks
"... Beamforming is a signal processing technique that enables antenna arrays to create directional signals, increasing transmitter or receiver gain. We propose a new adaptive user antenna beamforming technique for Multicell Cooperative Networks which simultaneously communicates with multiple available ..."
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Beamforming is a signal processing technique that enables antenna arrays to create directional signals, increasing transmitter or receiver gain. We propose a new adaptive user antenna beamforming technique for Multicell Cooperative Networks which simultaneously communicates with multiple available BSs and RSs using the MS’s multiple antennas. We show that the proposed adaptive beamforming technique outperforms distributed beamforming by increasing the data rate with less degradation of the BER.
2006 IEEE Ninth International Symposium on Spread Spectrum Techniques and Applications How Many Bits of Feedback is Multiuser Diversity Worth in MIMO Downlink?
"... Abstract — The impact of multiuser diversity on MIMO downlink is generally measured in terms of two asymptotic quantities derived from the sumrate, namely the scaling law of the sumrate versus the number of users n (for a fixed signaltonoise ratio, SNR) and the multiplexing gain (i.e., asymptoti ..."
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Abstract — The impact of multiuser diversity on MIMO downlink is generally measured in terms of two asymptotic quantities derived from the sumrate, namely the scaling law of the sumrate versus the number of users n (for a fixed signaltonoise ratio, SNR) and the multiplexing gain (i.e., asymptotic growth of the sumrate versus SNR). Designing optimal strategies with respect to these two criteria requires the availability of Channel State Information (CSI) at the transmitter, which in turn demands feedback of information from receivers to the transmitter. An open question is: how many bits of feedback are really necessary to achieve optimality of these criteria, i.e., to fully exploit multiuser diversity? In this paper, the optimal scaling law of the sumrate with respect to n, for fixed SNR, fixed number of transmit antennas M and any number of receiving antennas N (i.e., M log log nN), is proved to be achievable with a deterministic feedback of only one bit per user. The impact of adding feedback bits is also investigated. Furthermore, it is shown that the optimal multiplexing gain of M is guaranteed if the total feedback per cell is proportional to the SNR (in dB). The proofs build on opportunistic beamforming and binary quantization of the signaltonoiseplusinterference ratio. I.
doi:10.1155/2009/102064 Research Article On ThroughputFairness Tradeoff in Virtual MIMO Systems with Limited Feedback
"... We investigate the performance of channelaware scheduling algorithms designed for the downlink of a wireless communication system. Our study focuses on a twotransmit antenna cellular system, where the base station can only rely on quantized versions of channel state information to carry out schedu ..."
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We investigate the performance of channelaware scheduling algorithms designed for the downlink of a wireless communication system. Our study focuses on a twotransmit antenna cellular system, where the base station can only rely on quantized versions of channel state information to carry out scheduling decisions. The motivation is to study the interaction between throughput and fairness of practical spatial multiplexing schemes when implemented using existing physical layer signaling, such as the one that exists in current wideband code division multiple access downlink. Virtual MIMO system selects at each time instant a pair of users that report orthogonal (quantized) channels. Closedform expressions for the achievable sumrate of three different channelaware scheduling rules are presented using an analytical framework that is derived in this work. Our analysis reveals that simple scheduling procedures allow to reap a large fraction (in the order of 80%) of the sumrate performance that greedy scheduling provides. This overall throughput performance is obtained without affecting considerably the optimal shortterm fairness behavior that the end users would perceive. Copyright © 2009 Alexis A. Dowhuszko et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 1.
Multiuser Aware Limited Feedback for MIMO Systems
"... Consider a wireless communication system where the base station has multiple antennas and users have a single antenna. For both the multiple access and broadcast channels, the sum capacity scales at best linearly with the number of antennas at the base station and double logarithmically with the num ..."
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Consider a wireless communication system where the base station has multiple antennas and users have a single antenna. For both the multiple access and broadcast channels, the sum capacity scales at best linearly with the number of antennas at the base station and double logarithmically with the number of users as the user pool grows asymptotically. Achieving this optimal capacity scaling potentially requires feedback of channel state information (CSI) from all users, leading to overflow of the feedback channel. This paper proposes a limited feedback strategy that provides feedback control such that a sum CSI feedback rate constraint is satisfied. It is proved that a wireless multiantenna system using the proposed limited feedback strategy achieves the optimal capacity scaling for both the multiple access and the broadcast channels despite the sum feedback rate constraint. I.
DRAFT
"... This paper studies the structure of downlink sumrate maximizing selective decentralized feedback policies for opportunistic beamforming under finite feedback constraints on the average number of mobile users feeding back. Firstly, it is shown that any sumrate maximizing selective decentralized fee ..."
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This paper studies the structure of downlink sumrate maximizing selective decentralized feedback policies for opportunistic beamforming under finite feedback constraints on the average number of mobile users feeding back. Firstly, it is shown that any sumrate maximizing selective decentralized feedback policy must be a threshold feedback policy. This result holds for all fading channel models with continuous distribution functions. Secondly, the resulting optimum threshold selection problem is analyzed in detail. This is a nonconvex optimization problem over finite dimensional Euclidean spaces. By utilizing the theory of majorization, an underlying Schurconcave structure in the sumrate function is identified, and the sufficient conditions for the optimality of homogenous threshold feedback policies are obtained. Applications of these results are illustrated for well known fading channel models such as Rayleigh, Nakagami and Rician fading channels, along with various engineering and design insights. Rather surprisingly, it is shown that using the same threshold value at all mobile users is not always a ratewise optimal feedback strategy, even for a network with identical mobile users experiencing statistically the same channel conditions. For the Rayleigh fading channel model, on the other hand, homogenous threshold feedback policies are proven to be ratewise optimal if multiple orthonormal data carrying beams are used to communicate with multiple mobile users simultaneously.