Limited feedback in massive MIMO systems: Exploiting channel correlations via noncoherent trellis-coded quantization

Choi, Junil; Love, David J.; Madhow, Upamanyu

doi:10.1109/ciss.2013.6552342

Cited by 11 publications

(8 citation statements)

References 24 publications

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“…The pilot symbol SNR was defined as ρ p /σ 2 w , the data symbol SNR was defined as ρ d /σ 2 w , and the two SNR values were the same throughout the simulation. The noise variance σ 2 w was determined according to the SNR value with ρ p = ρ d = 1, and the received SNR is defined as (13), which incorporates the effect of beamforming gain and imperfect channel estimation. The channel estimation performance for each of the considered methods was averaged over 1, 000 Monte Carlo runs.…”

Section: Numerical Resultsmentioning

confidence: 99%

“…Such overhead can limit the performance improvement that is expected in massive MIMO systems. There has been some work on channel estimation and channel state information (CSI) feedback techniques for FDD massive MIMO systems, based on compressive sensing [11], limited feedback [12], [13], and projected channels [14]. Also, to improve channel estimation performance, the problem of pilot beam design was investigated for massive MIMO systems under the assumption of closed-loop training [15], [16].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Pilot Beam Pattern Design for Channel Estimation in Massive MIMO Systems

Noh

Zoltowski

Sung

et al. 2014

IEEE J. Sel. Top. Signal Process.

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217

174

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In this paper, the problem of pilot beam pattern design for channel estimation in massive multiple-input multiple-output systems with a large number of transmit antennas at the base station is considered, and a new algorithm for pilot beam pattern design for optimal channel estimation is proposed under the assumption that the channel is a stationary Gauss-Markov random process. The proposed algorithm designs the pilot beam pattern sequentially by exploiting the properties of Kalman filtering and the associated prediction error covariance matrices and also the channel statistics such as spatial and temporal channel correlation. The resulting design generates a sequentially-optimal sequence of pilot beam patterns with low complexity for a given set of system parameters. Numerical results show the effectiveness of the proposed algorithm.Comment: 15 pages, 12 figures, Practical issues such as channel covariance matrix estimation are considere

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Section: Numerical Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Pilot Beam Pattern Design for Channel Estimation in Massive MIMO Systems

Noh

Zoltowski

Sung

et al. 2014

IEEE J. Sel. Top. Signal Process.

Self Cite

217

174

View full text Add to dashboard Cite

show abstract

“…That is the reason why massive MIMO is not practical frequency division duplexing, but can be applicable in time division duplexing domain. As an alternative solution, limited feedback can be used [10]. In addition, massive MIMO suffers from pilot contamination and thermal noise produced by neighboring cells [7].…”

Section: A Massive Mimo Systemsmentioning

confidence: 99%

Research challenges for 5G cellular architecture

Bojković

Bakmaz

2015

2015 12th International Conference on Telecommunication in Modern Satellite, Cable and Broadcasting Services (TELSIKS)

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Due to the centralized architecture of current cellular networks, the wireless link capacity as well as the bandwidth of the radio access and backhaul networks cannot practically cope with the exponential growth of mobile traffic. In order to meet this challenge, researches on the fifth generation (5G) cellular systems are highly anticipated in the next decade. Advanced technologies such as massive antennas and millimeterwave systems, as well as direct communications will have significant impact on design of new heterogeneous network architecture. Cloud computing has emerged as a promising solution for providing high energy and spectral efficiency across software defined radio networks, in which the virtualization of communication hardware and software elements place stress on architecture and protocols. This paper analyses the main challenges raised by the new vision of cellular architecture, particularly focusing on issues related to the key emerging radio technologies, direct communications, cloud computing, as well as support of massive access.

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“…These techniques exploit spatial correlation or closed-loop training to get improved estimation performance. If transmit channel adaptation is needed, FDD systems also require potentially substantial feedback overhead [8]- [10].…”

Section: Introductionmentioning

confidence: 99%

Optimal pilot beam pattern design for massive MIMO systems

Noh

Zoltowski

Sung

et al. 2013

2013 Asilomar Conference on Signals, Systems and Computers

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In this paper, channel estimation for massive multiple-input multiple-output (MIMO) systems with a large number of transmit antennas at the base station is considered, and a new algorithm for pilot beam pattern design for optimal channel estimation under the assumption of Gauss-Markov channel processes is proposed. The proposed algorithm designs the optimal pilot beam pattern sequentially by exploiting the statistics of the channel, antenna correlation, and temporal correlation. The algorithm provides a sequentially optimal sequence of pilot beam patterns for a given set of system parameters. Numerical results show the effectiveness of the proposed algorithm.

show abstract

Limited feedback in massive MIMO systems: Exploiting channel correlations via noncoherent trellis-coded quantization

Cited by 11 publications

References 24 publications

Pilot Beam Pattern Design for Channel Estimation in Massive MIMO Systems

Pilot Beam Pattern Design for Channel Estimation in Massive MIMO Systems

Research challenges for 5G cellular architecture

Optimal pilot beam pattern design for massive MIMO systems

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