Joint multiuser transmit-receive optimization using linear processing

Tenenbaum, Adam J.; Adve, Raviraj

doi:10.1109/icc.2004.1312557

Cited by 56 publications

(37 citation statements)

References 8 publications

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“…[3] extended the single-user scheme [4] to the multiuser system. However, without exploring the multiuser channel information, it simply treated the multiuser interference as the white noise.…”

Section: Introductionmentioning

confidence: 99%

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Robust Linear Processing for Downlink Multiuser MIMO System with Imperfectly Known Channel

Zhao

Peng

et al. 2008

2008 IEEE Wireless Communications and Networking Conference

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Abstract-In practical systems, due to the time-varying radio channel, the channel state information (CSI) may not be known well at both transmitters and receivers. For most of the current multiuser multiple-input multiple-output (MIMO) schemes, they suffer a significant degression on the performance due to the mismatch between the true and estimated CSI. To alleviate the performance penalty, a robust downlink multiuser MIMO scheme is proposed in this paper by exploiting the channel mean and antenna correlation. These channel statistics are more stable than the imperfect CSI estimation in the time-varying radio channel, and they are used, in the proposed scheme, to minimize the total mean squared error under the sum power constraint. Simulation results demonstrate that the proposed scheme effectively mitigates the performance loss due to the CSI mismatch.

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Section: Introductionmentioning

confidence: 99%

“…It introduced a channel error matrix to the cost function of [3], then found the solution which minimized the average cost. However, similar with [3], the multiuser interference was also treated as the white noise. Therefore, it is expected that the performance can be improved by exploring the multiuser information.…”

Section: Introductionmentioning

confidence: 99%

Robust Linear Processing for Downlink Multiuser MIMO System with Imperfectly Known Channel

Zhao

Peng

et al. 2008

2008 IEEE Wireless Communications and Networking Conference

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“…Among the existing MU-MIMO methods, linear processing techniques [1]- [4], such as zeroforcing (ZF) based joint-channel diagonalization (JCD) [1], [2] and minimum mean square error (MMSE)-based methods [3], [4], require simpler transceivers than those of nonliner processing. The ZF-based methods, which perfectly cancel inter-user-interferences, can obtain more throughput than MMSE-based methods when signal-to-noise ratio (SNR) is high.…”

Section: Introductionmentioning

confidence: 99%

Evaluation for Various Resource Allocation Methods for Multiuser-MIMO OFDMA Systems

Joung

Lee

2007

2007 IEEE 18th International Symposium on Personal, Indoor and Mobile Radio Communications

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A simple algorithm to select user-pair and allocate frequency band is proposed for multiuser-MIMO OFDMA systems. For sake of comparison, various resource allocation algorithms, such as max-throughput, best-fit, first-fit, and random-fit algorithm, are examined with regard to the system throughput, computational complexity, and fairness among the users. Computer simulation results show that the first-fit algorithm can achieve a large reduction of computation for resource allocation as well as good fairness among users, with only a small reduction of throughput.

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“…Similarly, the receiver multiplies the received signal with a decoding matrix to minimize multiuser interference. While the early works focused on minimizing the sum of the mean squared error (SMSE) across all users' signals [1]- [4], linear precoding to maximize sum data rate is also possible [5].…”

Section: Introductionmentioning

confidence: 99%

“…This paper focuses on linear precoding [1]- [5] where the signals to be transmitted are multiplied with a precoding matrix before transmission. Similarly, the receiver multiplies the received signal with a decoding matrix to minimize multiuser interference.…”

Section: Introductionmentioning

confidence: 99%

Multiuser linear precoding for cooperating base stations with asynchronous interference

Azzam¹,

Adve

2008

2008 42nd Annual Conference on Information Sciences and Systems

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Abstract-This paper addresses multiuser linear precoding using multiple cooperating base stations (BSs). All BSs, and potentially the users, are equipped with multiple antennas. Prior work in multiuser precoding with a single BS extensively uses a downlink/uplink duality that significantly reduces the computation load. Here we show that the presence of asynchronous interference, unfortunately always present due to multiple BSs, precludes a simple duality. This in turn complicates deriving the needed precoding matrices. Even when duality is assumed to exist, asynchronous interference has its implications on the convexity of the power allocation problem. An optimization formulation and several related simulations for the asynchronous case are presented, including one where duality is assumed and another wherein orthogonal frequency division multiplexing (OFDM) is used for transmission and its cyclic prefix is used to mitigate asynchronous reception for edge users.

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Joint multiuser transmit-receive optimization using linear processing

Cited by 56 publications

References 8 publications

Robust Linear Processing for Downlink Multiuser MIMO System with Imperfectly Known Channel

Robust Linear Processing for Downlink Multiuser MIMO System with Imperfectly Known Channel

Evaluation for Various Resource Allocation Methods for Multiuser-MIMO OFDMA Systems

Multiuser linear precoding for cooperating base stations with asynchronous interference

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