Abstract
In this paper, we consider large-scale MIMO systems and we define iterative receivers which use the simplicity-based detection algorithm referred to as Finite Alphabet Simplicity (FAS) algorithm. First, we focus on uncoded systems and we propose a novel successive interference cancellation algorithm with an iterative processing based on the shadow area principle and we optimize its parameters by exploiting the theoretical analysis of the detector output. Secondly, we assume FEC-encoded systems and we propose an iterative receiver based on a maximum likelihood-like detection with restricted candidate subset defined by the FAS algorithm output. We also introduce another receiver based on FAS detection whose criterion is penalized with the mean absolute error function. Simulations results show the efficiency of all proposed iterative receivers compared to the state-of-the-art methods.
Highlights
The expected exponential growth in the number of connected mobile machines and data traffic is motivating 5G designers to look for new technologies and approaches to meet the growing demand
For the forward error correction (FEC)-encoded large-scale MultipleInput Multiple-Output (MIMO), (iii) we reduce the complexity of maximum likelihood (ML) detection by restricting the candidate subset of the Finite Alphabet Simplicity (FAS)-algorithm output (iv) to further reduce the complexity of the receiver, we propose a second iterative receiver with a detection based on a regularization of the FAS criterion without pre-treatment of the FEC-decoder output (v) and whose regularization parameter is fixed analytically
To further reduce the receiver complexity, we propose a second receiver whose detection is based on a regularization of the FAS criterion
Summary
The expected exponential growth in the number of connected mobile machines and data traffic is motivating 5G designers to look for new technologies and approaches to meet the growing demand. The ML-like sphere decoding technique [2] involves an exhaustive search in the hypersphere, the dimensions of which remain high in the case of large-scale MIMO, resulting in detection that is impossible to solve from a complexity point of view. It is shown that when an overdetermined MIMO system is considered (the number of receive antennas is much higher than the number of transmit antennas), the linear detectors such as ZF and MMSE perform close to the optimum thanks to the channel hardening phenomenon and become attractive from an implementation point of view In this case the spectral efficiency is limited by the number of transmit antennas which must be low. Dirac delta function and the indicator function of a subset A are denoted by δ(·) and 1A(·) respectively
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