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39
Capacity Limits of MIMO Channels
 IEEE J. SELECT. AREAS COMMUN
, 2003
"... We provide an overview of the extensive recent results on the Shannon capacity of singleuser and multiuser multipleinput multipleoutput (MIMO) channels. Although enormous capacity gains have been predicted for such channels, these predictions are based on somewhat unrealistic assumptions about t ..."
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Cited by 217 (10 self)
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We provide an overview of the extensive recent results on the Shannon capacity of singleuser and multiuser multipleinput multipleoutput (MIMO) channels. Although enormous capacity gains have been predicted for such channels, these predictions are based on somewhat unrealistic assumptions about the underlying timevarying channel model and how well it can be tracked at the receiver, as well as at the transmitter. More realistic assumptions can dramatically impact the potential capacity gains of MIMO techniques. For timevarying MIMO channels there are multiple Shannon theoretic capacity definitions and, for each definition, different correlation models and channel information assumptions that we consider. We first provide a comprehensive summary of ergodic and capacity versus outage results for singleuser MIMO channels. These results indicate that the capacity gain obtained from multiple antennas heavily depends
From theory to practice: an overview of MIMO spacetime coded wireless systems
 IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
, 2003
"... This paper presents an overview of recent progress in the area of multipleinput–multipleoutput (MIMO) space–time coded wireless systems. After some background on the research leading to the discovery of the enormous potential of MIMO wireless links, we highlight the different classes of technique ..."
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Cited by 199 (5 self)
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This paper presents an overview of recent progress in the area of multipleinput–multipleoutput (MIMO) space–time coded wireless systems. After some background on the research leading to the discovery of the enormous potential of MIMO wireless links, we highlight the different classes of techniques and algorithms proposed which attempt to realize the various benefits of MIMO including spatial multiplexing and space–time coding schemes. These algorithms are often derived and analyzed under ideal independent fading conditions. We present the state of the art in channel modeling and measurements, leading to a better understanding of actual MIMO gains. Finally, the paper addresses current questions regarding the integration of MIMO links in practical wireless systems and standards.
Iterative Waterfilling for Gaussian Vector Multiple Access Channels
 IEEE Transactions on Information Theory
, 2001
"... This paper characterizes the capacity region of a Gaussian multiple access channel with vector inputs and a vector output with or without intersymbol interference. The problem of finding the optimal input distribution is shown to be a convex programming problem, and an efficient numerical algorithm ..."
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Cited by 190 (11 self)
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This paper characterizes the capacity region of a Gaussian multiple access channel with vector inputs and a vector output with or without intersymbol interference. The problem of finding the optimal input distribution is shown to be a convex programming problem, and an efficient numerical algorithm is developed to evaluate the optimal transmit spectrum under the maximum sum data rate criterion. The numerical algorithm has an it#8 at#8 e wat#8filling int#j pret#4968 . It converges from any starting point and it reaches with in s per output dimension per transmission from the Kuser multiple access sum capacity af t#j just one it#4 at#49 . These results are also applicable to vector multiple access fading channels.
Sum capacity of the vector Gaussian broadcast channel and uplinkdownlink duality
 IEEE Trans. on Inform. Theory
, 1912
"... We characterize the sum capacity of the vector Gaussian broadcast channel by showing that the existing inner bound of Marton and the existing upper bound of Sato are tight for this channel. We exploit an intimate fourway connection between the vector broadcast channel, the corresponding pointtopo ..."
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Cited by 175 (2 self)
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We characterize the sum capacity of the vector Gaussian broadcast channel by showing that the existing inner bound of Marton and the existing upper bound of Sato are tight for this channel. We exploit an intimate fourway connection between the vector broadcast channel, the corresponding pointtopoint channel (where the receivers can cooperate), the multiple access channel (where the role of transmitters and receivers are reversed), and the corresponding pointtopoint channel (where the transmitters can cooperate). 1
Zeroforcing methods for downlink spatial multiplexing in multiuser MIMO channels
 IEEE Trans. Signal Processing
, 2004
"... Abstract—The use of spacedivision multiple access (SDMA) in the downlink of a multiuser multipleinput, multipleoutput (MIMO) wireless communications network can provide a substantial gain in system throughput. The challenge in such multiuser systems is designing transmit vectors while considering ..."
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Cited by 117 (4 self)
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Abstract—The use of spacedivision multiple access (SDMA) in the downlink of a multiuser multipleinput, multipleoutput (MIMO) wireless communications network can provide a substantial gain in system throughput. The challenge in such multiuser systems is designing transmit vectors while considering the cochannel interference of other users. Typical optimization problems of interest include the capacity problem—maximizing the sum information rate subject to a power constraint—or the power control problem—minimizing transmitted power such that a certain qualityofservice metric for each user is met. Neither of these problems possess closedform solutions for the general multiuser MIMO channel, but the imposition of certain constraints can lead to closedform solutions. This paper presents two such constrained solutions. The first, referred to as “blockdiagonalization,” is a generalization of channel inversion when there are multiple antennas at each receiver. It is easily adapted to optimize for either maximum transmission rate or minimum power and approaches the optimal solution at high SNR. The second, known as “successive optimization, ” is an alternative method for solving the power minimization problem one user at a time, and it yields superior results in some (e.g., low SNR) situations. Both of these algorithms are limited to cases where the transmitter has more antennas than all receive antennas combined. In order to accommodate more general scenarios, we also propose a framework for coordinated transmitterreceiver processing that generalizes the two algorithms to cases involving more receive than transmit antennas. While the proposed algorithms are suboptimal, they lead to simpler transmitter and receiver structures and allow for a reasonable tradeoff between performance and complexity. Index Terms—Antenna arrays, array signal processing, MIMO systems, signal design, space division multiaccess (SDMA), wireless LAN. I.
Exploiting Decentralized Channel State Information for Random Access
, 2002
"... We study the use of channel state information for random access in fading channels. Traditionally, random access protocols have been designed by assuming simple models for the physical layer where all users are symmetric and there is no notion of channel state. We introduce a reception model that ta ..."
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Cited by 60 (18 self)
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We study the use of channel state information for random access in fading channels. Traditionally, random access protocols have been designed by assuming simple models for the physical layer where all users are symmetric and there is no notion of channel state. We introduce a reception model that takes into account the channel states of various users. Under the assumption that each user has access to his channel state information (CSI), we propose a variant of Slotted ALOHA protocol for medium access control, where the transmission probability is allowed to be a function of the CSL The function is called the transmission control scheme. Assuming the finite user infinite buffer model we derive expressions for the maximum stable throughput of the system. We introduce the notion of asymptotic stable throughput (AST) that is the maximum stable throughput as the number of users goes to infinity. We consider two types of transmission control namely population independent transmission control (PITC) where the transmission control is not a function of the size of the network and population dependent transmission control where the transmission control is a function of the size of the network. We obtain expressions for the AST achievable with PITC. For population dependent transmission control, we introduce a particular transmission control that can potentially lead to significant gains in AST. For both PITC and PDTC, we show that the effect of transmission control is equivalent to changing the probability distribution of the channel state. The theory is then applied to CDMA networks with Linear Minimum Mean Square Error (LMMSE) receivers and Matched Filters (MF) to illustrate the effectiveness of utilizing channel state. It is shown that through the use of channel state, with an...
Precoding in MultiAntenna and MultiUser Communications
"... In this paper, TomlinsonHarashima precoding for multipleinput/multipleoutput systems including multipleantenna and multiuser systems is studied. It is shown that nonlinear preequalization offers significant advantages over linear preequalization which increases average transmit power. Moreover ..."
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Cited by 51 (1 self)
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In this paper, TomlinsonHarashima precoding for multipleinput/multipleoutput systems including multipleantenna and multiuser systems is studied. It is shown that nonlinear preequalization offers significant advantages over linear preequalization which increases average transmit power. Moreover, it outperforms decisionfeedback equalization at the receiver side which is applicable if joint processing at the receiver side is possible, and which suffers from error propagation. A number of aspects of practical importance are studied. Loading, i.e., the optimum distribution of transmit power and rate is discussed in detail. It is shown that the capacity of the underlying MIMO channel can be utilized asymptotically by means of nonlinear precoding.
Sum Capacity of the Multiple Antenna Gaussian Broadcast Channel And UplinkDownlink Duality
 IEEE Transactions on Information Theory
, 2002
"... We characterize the sum capacity of the multiple antenna Gaussian broadcast channel by showing that the existing inner bound of Marton and the existing upper bound of Sato are tight for this channel. We exploit an intimate fourway connection between the multiple antenna broadcast channel, the corre ..."
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Cited by 34 (4 self)
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We characterize the sum capacity of the multiple antenna Gaussian broadcast channel by showing that the existing inner bound of Marton and the existing upper bound of Sato are tight for this channel. We exploit an intimate fourway connection between the multiple antenna broadcast channel, the corresponding pointtopoint channel (where the receivers can cooperate), the multiple access channel (where the role of transmitters and receivers are reversed), and the corresponding pointtopoint channel (where the transmitters can cooperate).
SpaceTime Multiple Access: Linear Growth in the Sum Rate
 in Proc. 40th Annual Allerton Conf. Communications, Control and Computing
, 2002
"... It is known that some of the spectacular capacity gains of using multiple antennas on a pointtopoint rich scattering channel, namely linear growth with the number of antennas, can also be obtained in a multiuser environment. We give the constant of proportionality of linear growth in the sumcapa ..."
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Cited by 31 (7 self)
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It is known that some of the spectacular capacity gains of using multiple antennas on a pointtopoint rich scattering channel, namely linear growth with the number of antennas, can also be obtained in a multiuser environment. We give the constant of proportionality of linear growth in the sumcapacity when the number of users and antennas grow simultaneously, but with fewer users than antennas. We assume that the transmitter and receivers know the channel. Because of the linear growth in sumcapacity, we can accommodate more users simply by adding more antennas, without increasing total transmitted power or bandwidth or lowering the rate to existing users. We dub any scheme that can achieve linear growth in this fashion a spacetime multiple access scheme. Channelhardening arguments show that a "channelinversion" technique used in pointtopoint multipleantenna links achieves a large fraction of this linear growth in a multiuser environment without excessive transmitter power. Thus, multipleantennas offer a tremendous advantage in designing scheduling, networking, and multipleaccess protocols in rich scattering environments.