相关论文: Optimization of MIMO detectors: Unleashing the mul…

MIMO systems can simultaneously transmit multiple data streams within the same frequency band, thus exploiting the spatial dimension to enhance performance. MIMO detection poses considerable challenges due to the interference and noise…

In this paper, we propose a learning-based detection framework for uplink massive multiple-input and multiple-output (MIMO) systems with one-bit analog-to-digital converters. The learning-based detection only requires counting the…

Maximum-likelihood (ML) detection in high-order MIMO systems is computationally prohibitive due to exponential complexity in the number of transmit layers and constellation size. In this white paper, we demonstrate that for practical MIMO…

Massive multiple-input multiple-output (MIMO) systems are cellular networks where the base stations (BSs) are equipped with unconventionally many antennas. Such large antenna arrays offer huge spatial degrees-of-freedom for transmission…

Cell-free massive multiple-input-multiple-output (mMIMO) is an emerging technology for beyond 5G with its promising features such as higher spectral efficiency and superior spatial diversity as compared to conventional…

In this paper, we present a low-complexity algorithm for detection in high-rate, non-orthogonal space-time block coded (STBC) large-MIMO systems that achieve high spectral efficiencies of the order of tens of bps/Hz. We also present a…

We introduce a revised derivation of the bitwise Markov Chain Monte Carlo (MCMC) multiple-input multiple-output (MIMO) detector. The new approach resolves the previously reported high SNR stalling problem of MCMC without the need for…

This paper proposes spatial lattice modulation (SLM), a spatial modulation method for multipleinput-multiple-output (MIMO) systems. The key idea of SLM is to jointly exploit spatial, in-phase, and quadrature dimensions to modulate…

We propose a novel scheme that allows MIMO system to modulate a set of permutation matrices to send more information bits, extending our initial work on the topic. This system is called Permutation Matrix Modulation (PMM). The basic idea is…

In this paper, a cluster-aware two-stage multiple-input multiple-output (MIMO) detection method is proposed for direct-to-cell satellite communications. The method achieves computational efficiency by exploiting a distinctive property of…

In this paper, we propose a deep unfolding neural network-based MIMO detector that incorporates complex-valued computations using Wirtinger calculus. The method, referred as Dynamic Partially Shrinkage Thresholding (DPST), enables…

Multiple-input multiple-output orthogonal frequency division multiplexing with index modulation (MIMO-OFDM-IM) is a novel multicarrier transmission technique which has been proposed recently as an alternative to classical MIMO-OFDM. In this…

This paper derives a novel pilot-aided phase and channel estimation algorithm for multiple-input multiple-output (MIMO) systems with phase noise and quasi-static channel fading. Our novel approach allows, for the first time, carrier phase…

In this paper, a joint design of instantaneous channel estimation, beam tracking, and adaptive beamformer construction for a massive multiple-input multiple-output (MIMO) system is proposed. This design focuses on efficiency in terms of…

This paper studies a two-layer decoding method that mitigates inter-cell interference in multi-cell Massive MIMO systems. In layer one, each base station (BS) estimates the channels to intra-cell users and uses the estimates for local…

In this paper, we propose a model-driven deep learning network for multiple-input multiple-output (MIMO) detection. The structure of the network is specially designed by unfolding the iterative algorithm. Some trainable parameters are…

We carry out a theoretical analysis of the uplink (UL) of a massive MIMO system with per-user channel correlation and Rician fading, using two processing approaches. Firstly, we examine the linear minimum-mean-square-error receiver under…

We propose a soft-output detection scheme for Multiple-Input-Multiple-Output (MIMO) systems. The detector employs Markov Chain Monte Carlo method to compute bit reliabilities from the signals received and is thus suited for coded MIMO…

This thesis considers channel estimation and multiuser (MU) data transmission for massive MIMO systems with fully digital/hybrid structures in mmWave channels. It contains three main contributions. In this thesis, we first propose a…

A novel detector for multiple-input multiple-output (MIMO) communications is presented. The algorithm belongs to the class of the lattice detectors, i.e. it finds a reduced complexity solution to the problem of finding the closest vector to…