On the Multiplexing Gain of Discrete-Time MIMO Phase Noise Channels

Yang, Sheng; Shamai, Shlomo

doi:10.1109/tit.2017.2653718

Cited by 11 publications

(5 citation statements)

References 20 publications

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“…We only provide the proof for model B1, with both transmit and receive phase noises. The other cases are proved in the full paper [11]. Note that the multiplexing gain of this case is upperbounded by that of case B2 and case B3, since we can enhance the channel by providing the information on the transmit or receive phase noises to both the transmit and receiver.…”

Section: B Capacity Upper Bound For Model Bmentioning

confidence: 84%

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On MIMO phase noise channels at high SNR

Yang¹,

Shamai

2016

2016 IEEE Information Theory Workshop (ITW)

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We consider the point-to-point multi-input-multipleoutput (MIMO) channel with phase uncertainty (MIMO phase noise channel) at high SNR. With phase noise on the individual paths of the channel (model A), we show that the multiplexing gain is 1 2 , which implies that the capacity does not scale with the channel dimension at high SNR. With phase noise at both the input and output of the channel (model B), the multiplexing gain is upper-bounded by 1 2 min{nt, (nr − 2) + + 1}, and lowerbounded by 1 2 min{nt, nr+1 2 }, where nt and nr are the number of transmit and receive antennas, respectively. The multiplexing gain is enhanced to 1 2 min{nt, nr} without receive phase noise, and to 1 2 min{2nt − 1, nr} without transmit phase noise. Our main results rely on the derivation of non-trivial upper and lower bounds on the capacity of such channels.

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Section: B Capacity Upper Bound For Model Bmentioning

confidence: 84%

“…We prove the lower bound for model B in section IV. Concluding remarks are given in Section V. Due to the lack of space, proofs of the lemmas and some technical steps are omitted and can be found in the full version of the paper [11].…”

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confidence: 99%

On MIMO phase noise channels at high SNR

Yang¹,

Shamai

2016

2016 IEEE Information Theory Workshop (ITW)

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“…We leverage the following result from the phase noise literature for a key insight. Lemma 2 ( [36]): Let Φ = [e jθ1 , . .…”

Section: B Information Dimension Of W Via a Connection To The Mimo Ph...mentioning

confidence: 99%

Degree-of-Freedom of Modulating Information in the Phases of Reconfigurable Intelligent Surface

Cheng¹,

Yu²

2021

Preprint

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This paper investigates the information theoretical limit of a reconfigurable intelligent surface (RIS) aided communication scenario in which the RIS and the transmitter either jointly or independently send information to the receiver. The RIS is an emerging technology that uses a large number of passive reflective elements with adjustable phases to intelligently reflect the transmit signal to the intended receiver. While most previous studies of the RIS focus on its ability to beamform and to boost the received signal-to-noise ratio (SNR), this paper shows that if the information data stream is also available at the RIS and can be modulated through the adjustable phases at the RIS, significant improvement in the degree-of-freedom (DoF) of the overall channel is possible. For example, for an RIS system in which the signals are reflected from a transmitter with M antennas to a receiver with K antennas through an RIS with N reflective elements, assuming no direct path between the transmitter and the receiver, joint transmission of the transmitter and the RIS can achieve a DoF of min(M + N 2 − 1 2 , N, K) as compared to the DoF of min(M, K) for the conventional multipleinput multiple-output (MIMO) channel. This result is obtained by establishing a connection between the RIS system and the MIMO channel with phase noises and by using results for characterizing the information dimension under projection. The result is further extended to the case with a direct path between the transmitter and the receiver, and also to the multiple access scenario, in which the transmitter and the RIS send independent information. Finally, this paper proposes a symbol-level precoding approach for modulating data through the phases of the RIS, and provides numerical simulation results to verify the theoretical DoF results.

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“…The performance degradation due to phase noise becomes even more severe with the use of higher order modulations for which the angular separation between constellation points can be small. At medium to high SNR, phase noise dominates additive noise, becoming the capacity bottleneck [9], [10]. As for signal detection, finding the ML solution for the MIMO phase noise channel (1) is hard in general.…”

Section: Introductionmentioning

confidence: 99%

An Approximate ML Detector for MIMO Channels Corrupted by Phase Noise

Combes¹,

Yang²

2018

IEEE Trans. Commun.

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We consider the multiple-input multiple-output (MIMO) communication channel impaired by phase noises at both the transmitter and receiver. We focus on the maximum likelihood (ML) detection problem for uncoded single-carrier transmission. We derive an approximation of the likelihood function, based on which we propose an efficient detection algorithm. The proposed algorithm, named self-interference whitening (SIW), consists in 1) estimating the self-interference caused by the phase noise perturbation, then 2) whitening the said interference, and finally 3) detecting the transmitted vector. While the exact ML solution is computationally intractable, we construct a simulation-based lower bound on the error probability of ML detection. Leveraging this lower bound, we perform extensive numerical experiments demonstrating that SIW is, in most cases of interest, very close to optimal with moderate phase noise.More importantly and perhaps surprisingly, such near-ML performance can be achieved by applying only twice the nearest neighbor detection algorithm. In this sense, our results reveal a striking fact: near-ML detection of phase noise corrupted MIMO channels can be done as efficiently as for conventional MIMO channels without phase noise. Index TermsMIMO systems, phase noise, maximum likelihood detection, probability of error.The authors are with the

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On the Multiplexing Gain of Discrete-Time MIMO Phase Noise Channels

Cited by 11 publications

References 20 publications

On MIMO phase noise channels at high SNR

On MIMO phase noise channels at high SNR

Degree-of-Freedom of Modulating Information in the Phases of Reconfigurable Intelligent Surface

An Approximate ML Detector for MIMO Channels Corrupted by Phase Noise

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