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96
Degrees of freedom region of the MIMO . . .
, 2008
"... We provide achievability as well as converse results for the degrees of freedom region of a multipleinput multipleoutput (MIMO) X channel, i.e., a system with two transmitters, two receivers, each equipped with multiple antennas, where independent messages need to be conveyed over fixed channels fr ..."
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Cited by 32 (6 self)
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We provide achievability as well as converse results for the degrees of freedom region of a multipleinput multipleoutput (MIMO) X channel, i.e., a system with two transmitters, two receivers, each equipped with multiple antennas, where independent messages need to be conveyed over fixed channels from each transmitter to each receiver. The inner and outer bounds on the degrees of freedom region are tight whenever integer degrees of freedom are optimal for each message. With M =1antennas at each node, we find that the total (sum rate) degrees of freedom are bounded above and below as 1? 4 X.IfM>1 and channel
On the capacity of fading MIMO broadcast channels with imperfect transmitter sideinformation
 in Annual Allerton Conference on Communication, Control, and Computing
, 2005
"... A fading broadcast channel is considered where the transmitter employs two antennas and each of the two receivers employs a single receive antenna. It is demonstrated that even if the realization of the fading is precisely known to the receivers, the high signaltonoise (SNR) throughput is greatly ..."
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Cited by 31 (2 self)
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A fading broadcast channel is considered where the transmitter employs two antennas and each of the two receivers employs a single receive antenna. It is demonstrated that even if the realization of the fading is precisely known to the receivers, the high signaltonoise (SNR) throughput is greatly reduced if, rather than knowing the fading realization precisely, the trasmitter only knows the fading realization approximately. The results are general and are not limited to memoryless Gaussian fading. 1
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 27 (9 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 transmitter 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 nonlinear and linear channelaware 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
Degrees of freedom region of the MIMO X Channel
, 2007
"... hop, is especially interesting, as the intermediate hop takes place over an interference channel with single antenna nodes. While the two user interference channel with single antenna nodes has only one degree of freedom by itself, it is able to deliver degrees of freedom when used as an intermediat ..."
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Cited by 26 (10 self)
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hop, is especially interesting, as the intermediate hop takes place over an interference channel with single antenna nodes. While the two user interference channel with single antenna nodes has only one degree of freedom by itself, it is able to deliver degrees of freedom when used as an intermediate stage between a antenna source and a antenna destination [5]. The key is an amplify and forward scheme where the relay nodes, instead of trying to decode the messages, simply scale and forward their received signals. [1]–[3] consider end to end channel orthogonalization with distributed sources, relays and destination nodes and determine the capacity scaling behavior with the number of relay nodes. It is shown that distributed orthogonalization can be obtained even with synchronization errors if a minimum amount of coherence at the relays can be sustained. Degrees of freedom for linear interference networks with local sideinformation are explored in [22] and cognitive message sharing is found to improve the degrees of freedom for certain structured channel matrices. The MIMO MAC and BC channels show that there is no loss in degrees of freedom even if antennas are distributed among users at one end (either transmitters or receivers) making joint signal processing infeasible, as long as joint signal processing is possible at the other end of the communication link. The multiple hop example of [5], described above, shows that there is no loss of degrees of freedom even with distributed antennas at both ends of a communication hop (an interference channel) as long as the distributed antenna stages are only intermediate
MIMO wireless linear precoding
 IEEE Signal Processing Magazine
, 2006
"... The benefits of using multiple antennas at both the transmitter and the receiver in a wireless system are well established. Multipleinput multipleoutput (MIMO) systems enable a growth in transmission rate linear in the minimum of the number of antennas at either end [1][2]. MIMO techniques also en ..."
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Cited by 23 (0 self)
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The benefits of using multiple antennas at both the transmitter and the receiver in a wireless system are well established. Multipleinput multipleoutput (MIMO) systems enable a growth in transmission rate linear in the minimum of the number of antennas at either end [1][2]. MIMO techniques also enhance link reliability and
Finiterate feedback MIMO broadcast channels with a large number of users
 Proc. of IEEE Intl. Symposium on Info. Theory
, 2006
"... Abstract — We analyze the sumrate performance of a multiantenna 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 ..."
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Cited by 23 (3 self)
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Abstract — We analyze the sumrate performance of a multiantenna 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 sumrate 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. I.
On the compound mimo broadcast channel
 in Proceedings of Annual Information Theory and Applications Workshop UCSD
, 2007
"... Abstract — We consider the Gaussian multiantenna compound broadcast channel where one transmitter transmits several messages, each intended for a different user whose channel realization is arbitrarily chosen from a finite set. Our investigation focuses on the behavior of this channel at high SNRs ..."
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Cited by 21 (0 self)
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Abstract — We consider the Gaussian multiantenna compound broadcast channel where one transmitter transmits several messages, each intended for a different user whose channel realization is arbitrarily chosen from a finite set. Our investigation focuses on the behavior of this channel at high SNRs and we obtain the multiplexing gain of the sum capacity for a number of cases, and point out some implications of the total achievable multiplexing gain region. 1 I.
MultiAntenna Broadcast Channels with Limited Feedback and User Selection
, 2006
"... We analyze the sumrate performance of a multiantenna 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 20 (3 self)
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We analyze the sumrate performance of a multiantenna 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 sumrate 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.
Space division multiple access with a sum feedback rate constraint
 IEEE Trans. Signal Processing
, 2007
"... Abstract—On a multiantenna broadcast channel, simultaneous transmission to multiple users by joint beamforming and scheduling is capable of achieving high throughput, which grows double logarithmically with the number of users. The sum rate for channel state information (CSI) feedback, however, incr ..."
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Cited by 18 (2 self)
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Abstract—On a multiantenna broadcast channel, simultaneous transmission to multiple users by joint beamforming and scheduling is capable of achieving high throughput, which grows double logarithmically with the number of users. The sum rate for channel state information (CSI) feedback, however, increases linearly with the number of users, reducing the effective uplink capacity. To address this problem, a novel space division multiple access (SDMA) design is proposed, where the sum feedback rate is upper bounded by a constant. This design consists of algorithms for CSI quantization, thresholdbased CSI feedback, and joint beamforming and scheduling. The key feature of the proposed approach is the use of feedback thresholds to select feedback users with large channel gains and small CSI quantization errors such that the sum feedback rate constraint is satisfied. Despite this constraint, the proposed SDMA design is shown to achieve a sum capacity growth rate close to the optimal one. Moreover, the feedback overflow probability for this design is found to decrease exponentially with the difference between the allowable and the average sum feedback rates. Numerical results show that the proposed SDMA design is capable of attaining higher sum capacities than existing ones, even though the sum feedback rate is bounded. Index Terms—Broadcast channels, feedback communication, multiuser channels, space division multiplexing. I.
Joint beamforming and scheduling for a multiantenna downlink with imperfect transmitter channel knowledge
 IEEE J. Select. Areas Commun
, 2007
"... We consider the downlink of a wireless system where the basestation has M ≥ 1 antennas and K user terminals have one antenna each. We study the weighted rate sum maximization in the case of nonperfect Channel State Information at the Transmitter (CSIT). Some relevant downlink optimization problems ..."
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Cited by 17 (3 self)
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We consider the downlink of a wireless system where the basestation has M ≥ 1 antennas and K user terminals have one antenna each. We study the weighted rate sum maximization in the case of nonperfect Channel State Information at the Transmitter (CSIT). Some relevant downlink optimization problems, such as the stabilization of the transmission queues under random packet arrivals and the proportional fair scheduling for infinite backlogged systems, can be solved as special cases of the proposed problem. We restrict the transmitter strategy to be based on Gaussian coding and beamforming. Even under this simplifying condition, the problem at hand is nonconvex and it does not appear to lend itself to a simple algorithmic solution. Therefore, we introduce some approximations that yield a definition of signaltointerference plus noise ratio (SINR) commonly used in the classical arrayprocessing/beamforming literature. For the simpler (but still nonconvex) approximated problem, we propose a powerful heuristic solution based on greedy user selection and a gradient iteration that converges to a local maximum of the objective function. This method yields very competitive results with relatively low computational complexity. Extensive simulations show that, in the case of perfect CSIT, the proposed heuristic scheme performs very closely to the optimal (dirtypaper coding) strategy while, in the case of nonperfect CSIT, it significantly outperforms previously proposed suboptimal approaches, such as random beamforming and approximated zeroforcing with greedy user selection.