Limited feedback scheme based on adaptive codebook for spatially and temporally correlated MIMO channels

2011 ◽  
Author(s):  
Yu Huang ◽  
Xiaodong Ji ◽  
Mugen Peng
Keyword(s):  
Limited Feedback ◽  
Mimo Channels ◽  
Feedback Scheme ◽  
Adaptive Codebook ◽  
Temporally Correlated

scholarly journals Decentralized Limited-Feedback Multiuser MIMO for Temporally Correlated Channels

2010 ◽  
Vol 2010 ◽  
pp. 1-9
Author(s):  
Eduardo Zacarías B ◽  
Stefan Werner ◽  
Risto Wichman
Keyword(s):  
Multiple Input Multiple Output ◽  
Limited Feedback ◽  
Mimo Channels ◽  
Linear Filters ◽  
Correlated Channels ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Channel Information ◽  
Feedback Algorithm ◽  
Temporally Correlated

This paper proposes a novel multiuser (MU) multiplexing scheme for temporally correlated multiple-input, multiple-output (MIMO) channels, suitable for systems employing low-rate feedback links. A decentralized solution is obtained by the mobile receivers, which employ interference rejection combiner (IRC) linear filters and command the update of the corresponding per-user antenna transmit weights through compact feedback messages, thus avoiding explicit transmission of channel information. The proposed limited-feedback algorithm outperforms existing MU-MIMO solutions employing quantized matrices, operating at the same feedback overhead. A compensation mechanism is presented, which enables the proposed solution to operate under moderate probabilities of feedback errors, at the expense of a small downlink overhead.

On Source Transmission Over MIMO Channels With Limited Feedback

2009 ◽  
Vol 57 (1) ◽  
pp. 324-341 ◽  
Author(s):  
T.T. Kim ◽  
M. Skoglund ◽  
G. Caire
Keyword(s):  
Limited Feedback ◽  
Mimo Channels

scholarly journals Channel Prediction for Mobile MIMO Wireless Communication Systems

2021 ◽  
Author(s):  
◽  
Ramoni Ojekunle Adeogun
Keyword(s):  
Wireless Communication ◽  
Temporal Variation ◽  
Prediction Error ◽  
Communication Systems ◽  
Limited Feedback ◽  
Wireless Communication Systems ◽  
Performance Bounds ◽  
Mimo Channels ◽  
Channel Prediction ◽  
Estimation And Prediction

<p>Temporal variation and frequency selectivity of wireless channels constitute a major drawback to the attainment of high gains in capacity and reliability offered by multiple antennas at the transmitter and receiver of a mobile communication system. Limited feedback and adaptive transmission schemes such as adaptive modulation and coding, antenna selection, power allocation and scheduling have the potential to provide the platform of attaining the high transmission rate, capacity and QoS requirements in current and future wireless communication systems. Theses schemes require both the transmitter and receiver to have accurate knowledge of Channel State Information (CSI). In Time Division Duplex (TDD) systems, CSI at the transmitter can be obtained using channel reciprocity. In Frequency Division Duplex (FDD) systems, however, CSI is typically estimated at the receiver and fed back to the transmitter via a low-rate feedback link. Due to the inherent time delays in estimation, processing and feedback, the CSI obtained from the receiver may become outdated before its actual usage at the transmitter. This results in significant performance loss, especially in high mobility environments. There is therefore a need to extrapolate the varying channel into the future, far enough to account for the delay and mitigate the performance degradation. The research in this thesis investigates parametric modeling and prediction of mobile MIMO channels for both narrowband and wideband systems. The focus is on schemes that utilize the additional spatial information offered by multiple sampling of the wave-field in multi-antenna systems to aid channel prediction. The research has led to the development of several algorithms which can be used for long range extrapolation of time-varyingchannels. Based on spatial channel modeling approaches, simple and efficient methods for the extrapolation of narrowband MIMO channels are proposed. Various extensions were also developed. These include methods for wideband channels, transmission using polarized antenna arrays, and mobile-to-mobile systems. Performance bounds on the estimation and prediction error are vital when evaluating channel estimation and prediction schemes. For this purpose, analytical expressions for bound on the estimation and prediction of polarized and non-polarized MIMO channels are derived. Using the vector formulation of the Cramer Rao bound for function of parameters, readily interpretable closed-form expressions for the prediction error bounds were found for cases with Uniform Linear Array (ULA) and Uniform Planar Array (UPA). The derived performance bounds are very simple and so provide insight into system design. The performance of the proposed algorithms was evaluated using standardized channel models. The effects of the temporal variation of multipath parameters on prediction is studied and methods for jointly tracking the channel parameters are developed. The algorithms presented can be utilized to enhance the performance of limited feedback and adaptive MIMO transmission schemes.</p>

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