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322
From Single user to Multiuser Communications: Shifting the MIMO paradigm
- IEEE Sig. Proc. Magazine
, 2007
"... In multiuser MIMO networks, the spatial degrees of freedom offered by multiple antennas can be advantageously exploited to enhance the system capacity, by scheduling multiple users to simultaneously share the spatial channel. This entails a fundamental paradigm shift from single user communications, ..."
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Cited by 46 (13 self)
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In multiuser MIMO networks, the spatial degrees of freedom offered by multiple antennas can be advantageously exploited to enhance the system capacity, by scheduling multiple users to simultaneously share the spatial channel. This entails a fundamental paradigm shift from single user communications, since multiuser systems can experience substantial benefit from channel state information at the transmit-ter and, at the same time, require more complex scheduling strategies and transceiver methodologies. This paper reviews multiuser MIMO communication from an algorithmic perspective, discussing performance gains, tradeoffs, and practical considerations. Several approaches including non-linear and linear channel-aware precoding are reviewed, along with more practical limited feedback schemes that require only partial channel state information. The interaction between precoding and scheduling is discussed. Several promising strategies for limited multiuser feedback design are looked at, some of which are inspired from the single user MIMO precoding scenario while others are fully specific to the multiuser setting. 1 DRAFT
Rate maximization in multiantenna broadcast channels with linear preprocessing
- in Proc. IEEE Globecom
"... Abstract — The sum rate capacity of the multi-antenna broadcast channel has recently been computed. However, the search for efficient practical schemes that achieve it is still ongoing. In this paper, we focus on schemes with linear preprocessing of the transmitted data. We propose two criteria for ..."
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Cited by 42 (0 self)
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Abstract — The sum rate capacity of the multi-antenna broadcast channel has recently been computed. However, the search for efficient practical schemes that achieve it is still ongoing. In this paper, we focus on schemes with linear preprocessing of the transmitted data. We propose two criteria for the precoding matrix design: one maximizing the sum rate and the other maximizing the minimum rate among all users. The latter problem is shown to be quasiconvex and is solved exactly via a bisection method. In addition to precoding, we employ a signal scaling scheme that minimizes the average bit-error-rate (BER). The signal scaling scheme is posed as a convex optimization problem, and thus can be solved exactly via efficient interiorpoint methods. In terms of the achievable sum rate, the proposed technique significantly outperforms traditional channel inversion methods, while having comparable (in fact, often superior) BER performance. Index Terms — Multi-antenna broadcast channel, convex problem, quasiconvex problem, bisection method, interior-point method. I.
Distributed Downlink Beamforming With Cooperative Base Stations
- IEEE Trans. Inf. Theory
, 2008
"... Abstract—In this paper, we consider multicell processing on the downlink of a cellular network to accomplish “macrodiversity” transmit beamforming. The particular downlink beamformer structure we consider allows a recasting of the downlink beam-forming problem as a virtual linear mean square error ( ..."
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Cited by 41 (2 self)
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Abstract—In this paper, we consider multicell processing on the downlink of a cellular network to accomplish “macrodiversity” transmit beamforming. The particular downlink beamformer structure we consider allows a recasting of the downlink beam-forming problem as a virtual linear mean square error (LMMSE) estimation problem. We exploit the structure of the channel and develop distributed beamforming algorithms using local message passing between neighboring base stations. For 1-D networks, we use the Kalman smoothing framework to obtain a forward–back-ward beamforming algorithm. We also propose a limited extent version of this algorithm that shows that the delay need not grow with the size of the network in practice. For 2-D cellular networks, we remodel the network as a factor graph and present a distributed beamforming algorithm based on the sum–product algorithm. Despite the presence of loops in the factor graph, the algorithm produces optimal results if convergence occurs. Index Terms—Cooperative base stations, distributed algo-rithm, downlink beamforming, Kalman smoothing, linear mean square error (LMMSE), localized interference, message passing, multicell processing, multiple-input–multiple-output (MIMO), sum–product algorithm. I.
Linear precoding in cooperative MIMO cellular networks with limited coordination clusters
- IEEE J. Sel. Areas Commun
, 2010
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On the user selection in MIMO broadcast channels
- IN PROC. OF INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY
, 2005
"... In this paper, a downlink communication system, in which a Base Station (BS) equipped with M antennas communicates with N users each equipped with K receive antennas, is considered. An efficient suboptimum algorithm is proposed for selecting a set of users in order to maximize the sum-rate throughpu ..."
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Cited by 34 (5 self)
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In this paper, a downlink communication system, in which a Base Station (BS) equipped with M antennas communicates with N users each equipped with K receive antennas, is considered. An efficient suboptimum algorithm is proposed for selecting a set of users in order to maximize the sum-rate throughput of the system. For the asymptotic case when N tends to infinity, the necessary and sufficient conditions in order to achieve the maximum sum-rate throughput, such that the difference between the achievable sum-rate and the maximum value approaches zero, is derived. The complexity of our algorithm is investigated in terms of the required amount of feedback from the users to the base station, as well as the number of searches required for selecting the users. It is shown that the proposed method is capable of achieving a large portion of the sum-rate capacity, with a very low complexity.
Performance of conjugate and zero-forcing beamforming in large-scale antenna systems
- IEEE Journal on Selected Areas in Communications
, 2013
"... Abstract—Large-Scale Antenna Systems (LSAS) is a form of multi-user MIMO technology in which unprecedented numbers of antennas serve a significantly smaller number of autonomous terminals. We compare the two most prominent linear precoders, conjugate beamforming and zero-forcing, with respect to net ..."
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Cited by 33 (1 self)
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Abstract—Large-Scale Antenna Systems (LSAS) is a form of multi-user MIMO technology in which unprecedented numbers of antennas serve a significantly smaller number of autonomous terminals. We compare the two most prominent linear precoders, conjugate beamforming and zero-forcing, with respect to net spectral-efficiency and radiated energy-efficiency in a simplified single-cell scenario where propagation is governed by independent Rayleigh fading, and where channel-state information (CSI) acquisition and data transmission are both performed during a short coherence interval. An effective-noise analysis of the pre-coded forward channel yields explicit lower bounds on net capacity which account for CSI acquisition overhead and errors as well as the sub-optimality of the pre-coders. In turn the bounds generate trade-off curves between radiated energy-efficiency and net spectral-efficiency. For high spectralefficiency and low energy-efficiency zero-forcing outperforms conjugate beamforming, while at low spectral-efficiency and high energy-efficiency the opposite holds. Surprisingly, in an optimized system, the total LSAS-critical computational burden of conjugate beamforming may be greater than that of zeroforcing. Conjugate beamforming may still be preferable to zeroforcing because of its greater robustness, and because conjugate beamforming lends itself to a de-centralized architecture and de-centralized signal processing. Index Terms—Large-scale antenna system, capacity, energy efficiency, spectral efficiency, spatial multiplexing, beamforming, pre-coder, computational burden I.
Cooperative Multi-cell Block Diagonalization with Per-Base-Station Power Constraints
, 2010
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MIMO multichannel beamforming: SER and outage using new eigenvalue distributions of complex noncentral Wishart matrices
- IEEE Transactions on Communications
, 2008
"... This paper analyzes MIMO systems with multichannel beamforming in Ricean fading. Our results apply to a wide class of multichannel systems which transmit on the eigenmodes of the MIMO channel. We first present new closed-form expressions for the marginal ordered eigenvalue distributions of complex n ..."
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Cited by 31 (5 self)
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This paper analyzes MIMO systems with multichannel beamforming in Ricean fading. Our results apply to a wide class of multichannel systems which transmit on the eigenmodes of the MIMO channel. We first present new closed-form expressions for the marginal ordered eigenvalue distributions of complex noncentral Wishart matrices. These are used to characterize the statistics of the signal to noise ratio (SNR) on each eigenmode. Based on this, we present exact symbol error rate (SER) expressions. We also derive closed-form expressions for the diversity order, array gain, and outage probability. We show that the global SER performance is dominated by the subchannel corresponding to the minimum channel singular value. We also show that, at low outage levels, the outage probability varies inversely with the Ricean K-factor for cases where transmission is only on the most dominant subchannel (i.e. a singlechannel beamforming system). Numerical results are presented to validate the theoretical analysis.
Large System Analysis of Linear Precoding in MISO Broadcast Channels with Limited Feedback
, 2010
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Multi-Antenna Broadcast Channels with Limited Feedback and User Selection
, 2006
"... We analyze the sum-rate performance of a multi-antenna downlink system carrying more users than transmit antennas, with partial channel knowledge at the transmitter due to finite rate feedback. In order to exploit multiuser diversity, we show that the transmitter must have, in addition to directiona ..."
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Cited by 29 (3 self)
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We analyze the sum-rate performance of a multi-antenna downlink system carrying more users than transmit antennas, with partial channel knowledge at the transmitter due to finite rate feedback. In order to exploit multiuser diversity, we show that the transmitter must have, in addition to directional information, information regarding the quality of each channel. Such information should reflect both the channel magnitude and the quantization error. Expressions for the SINR distribution and the sum-rate are derived, and tradeoffs between the number of feedback bits, the number of users, and the SNR are observed. In particular, for a target performance, having more users reduces feedback load.
