Asymptotic Analysis of SU-MIMO Channels With Transmitter Noise and Mismatched Joint Decoding

Abstract

International audience—Hardware impairments in radio-frequency components of a wireless system cause unavoidable distortions to transmission that are not captured by the conventional linear channel model. In this paper, a " binoisy " single-user multiple-input multiple-output (SU-MIMO) relation is considered where the additional distortions are modeled via an additive noise term at the transmit side. Through this extended SU-MIMO channel model, the effects of transceiver hardware impairments on the achievable rate of multi-antenna point-to-point systems are studied. Channel input distributions encompassing practical discrete modulation schemes, such as, QAM and PSK, as well as Gaussian signaling are covered. In addition, the impact of mismatched detection and decoding when the receiver has insufficient information about the non-idealities is investigated. The numerical results show that for realistic system parameters, the effects of transmit-side noise and mismatched decoding become significant only at high modulation orders. Index Terms—Multiple antennas, mismatched decoding, ergodic capacity, fading channels, generalized mutual information (GMI), transceiver hardware impairments

Asymptotic Performance Analysis of a $K$ -Hop Amplify-and-Forward Relay MIMO Channel

“…The presented results are potentially extendable to more sophisticated channel models of interest (e.g., Kronecker model or Rician fading) allowing for further performance optimization as in [54]. Another practical problem of interest would be to consider the case of covariance mismatched decoding [45], where the receiver does not know the instantaneous realizations of the intermediate channels.…”

“…The case where the receiver is ignorant of the intermediate channels leads to mismatched decoding [43], [44]. For an application of covariance mismatched decoding in the context of large-scale MIMO systems, see for example, [45]. 5 To account for the TDMA protocol, a factor of 1/K is applied to (5).…”

Optimal large-MIMO data detection with transmit impairments

“…A corresponding asymptotic analysis has been provided recently in [21], which uses the replica method [22] to obtain capacity expressions for large MIMO systems. The results in [1], [21] build upon on the so-called Gaussian transmit-noise model, which assumes that the transmit impairments in e can be modeled as i.i.d. additive Gaussian noise that is independent of the transmit signal s. While the accuracy of this model for a particular RF implementation in a MIMO system using orthogonal frequency-division multiplexing (OFDM) has been confirmed via real-world measurements [1], it may not be accurate for other RF transceiver designs and/or modulation schemes.…”

Asymptotic analysis of asymmetric MIMO links: EVM limits for joint decoding of PSK and QAM

“…For finite M and N , the results should therefore be considered as approximations. The derivations have been omitted here due to space constraints but they can be found, among other complementing results, in the related journal article [20] and the current numerical results are new.…”

“…The analytic results, presented in a complete form in [20], allow us to study the rate loss due to EVM under joint decoding. The results cover all practical discrete modulation schemes for which QPSK, 8-PSK, and 16-QAM are used as examples in this paper.…”