Related papers: Low Complexity V-BLAST MIMO-OFDM Detector by Succe…
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…
This paper addresses a data detection problem for multiple-input multiple-output (MIMO) communication systems with hardware impairments. To facilitate maximum likelihood (ML) data detection without knowledge of nonlinear and unknown…
Multiple-input multiple-output (MIMO) is a key ingredient of next-generation wireless communications. Recently, various MIMO signal detectors based on deep learning techniques and quantum(-inspired) algorithms have been proposed to improve…
In this paper, an efficient massive multiple-input multiple-output (MIMO) detector is proposed by employing a deep neural network (DNN). Specifically, we first unfold an existing iterative detection algorithm into the DNN structure, such…
We study the performance of the simulated bifurcation (SB) algorithm for signal detection in multiple-input multiple-output (MIMO) system, a problem of key interest in modern wireless communication systems. Our results show that SB…
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…
A dual-layer multiple-input multiple-output (MIMO) system with multi-level modulation is considered. A computationally efficient soft-input soft-output receiver based on the exact max-log maximum a posteriori (max-log-MAP) principle is…
Due to high spectral efficiency and power efficiency, the continuous phase modulation (CPM) technique with constant envelope is widely used in aeronautical telemetry in strategic weapons and rockets, which are essential for national defence…
For many practical applications in wireless communications, we need to recover a structured sparse signal from a linear observation model with dynamic grid parameters in the sensing matrix. Conventional expectation maximization (EM)-based…
Tree-based demappers for multiple-input multiple-output (MIMO) detection such as the sphere decoder can achieve near-optimal performance but incur high computational cost due to their sequential nature. In this paper, we propose the…
This paper considers base station cooperation (BSC) strategies for the uplink of a multi-user multi-cell high frequency reuse scenario where distributed iterative detection (DID) schemes with soft/hard interference cancellation algorithms…
This paper proposes a novel modulation and coding scheme (MCS) selection framework that integrates mutual information (MI) prediction based on vector similarity search (VSS) for massive multi-user multiple-input multiple-output orthogonal…
We propose an adaptive learning-based framework for uplink massive multiple-input multiple-output (MIMO) systems with one-bit analog-to-digital converters. Learning-based detection does not need to estimate channels, which overcomes a key…
With a unified belief propagation (BP) and mean field (MF) framework, we propose an iterative message passing receiver, which performs joint channel state and noise precision (the reciprocal of noise variance) estimation and decoding for…
An accurate and computationally efficient SLAM algorithm is vital for modern autonomous vehicles. To make a lightweight the algorithm, most SLAM systems rely on feature detection from images for vision SLAM or point cloud for laser-based…
Classical ML decoders of MIMO systems like the sphere decoder, the Schnorr-Euchner algorithm, the Fano and the stack decoders suffer of high complexity for high number of antennas and large constellation sizes. We propose in this paper a…
The minimum degree algorithm is one of the most widely-used heuristics for reducing the cost of solving large sparse systems of linear equations. It has been studied for nearly half a century and has a rich history of bridging techniques…
An alternate direction method of multipliers (ADMM)-based detectors can achieve good performance in both small and large-scale multiple-input multiple-output (MIMO) systems. However, due to the difficulty of choosing the optimal penalty…
Herein, an atomic norm based method for accurately estimating the location and orientation of a target from millimeter-wave multi-input-multi-output (MIMO) orthogonal frequency-division multiplexing (OFDM) signals is presented. A novel…
A modulation classification (MC) scheme based on Independent Component Analysis (ICA) in conjunction with either maximum likelihood (ML) or Support Vector Machines (SVM) is proposed for MIMO-OFDM signals over frequency selective, time…