Related papers: Efficient Non-linear Equalization for 1-bit Quanti…
This work studies multiuser detection for one-bit massive multiple-input multiple-output (MIMO) systems in order to diminish the power consumption at the base station (BS). A low-complexity near-maximum-likelihood (nML) multiuser detection…
Massive MIMO systems are moving toward increased numbers of radio frequency chains, higher carrier frequencies and larger bandwidths. As such, digital-to-analog converters (DACs) are becoming a bottleneck in terms of hardware complexity and…
The deployment of large-scale antenna arrays for cellular base stations (BSs), termed as `Massive MIMO', has been a key enabler for meeting the ever-increasing capacity requirement for 5G communication systems and beyond. Despite their…
Massive multiple-input multiple-output low-Earth-orbit communication channels are highly time-varying due to severe Doppler shifts and propagation delays. While satellite-mobility-induced Doppler shifts can be compensated using known…
This paper presents an innovative approach to enhancing machine learning based communication systems, specifically focusing on multiple-input multiple-output (MIMO) configurations using autoencoders. We optimize the transmitter, receiver,…
Massive multi-input multi-output (MIMO) can support high spectral efficiency (SE) with simple linear transceivers, and is expected to provide high energy efficiency (EE). In this paper, we analyze the EE of downlink multi-cell massive MIMO…
Optimal MIMO detection has been one of the most challenging and computationally inefficient tasks in wireless systems. We show that the new analog computing techniques like Coherent Ising Machines (CIM) are promising candidates for…
Block transmission systems have been proven successful over frequency-selective channels. For time-varying channel such as in high-speed mobile communication and underwater communication, existing equalizers assume that channels over…
Block diagonalization is a linear precoding technique for the multiple antenna broadcast (downlink) channel that involves transmission of multiple data streams to each receiver such that no multi-user interference is experienced at any of…
In this paper, we solve the sum mean-squared error (MSE)-optimal 1-bit quantized precoding problem exactly for small-to-moderate sized multiuser multiple-input multiple-output (MU-MIMO) systems via branch and bound. To this end, we…
This paper studies the distributed optimal bilinear equalizer (OBE) beamforming design for both the uplink and downlink cell-free massive multiple-input multiple-output networks. We consider arbitrary statistics-based channel estimators…
Expectation-Maximization (EM) algorithm is a widely used iterative algorithm for computing maximum likelihood estimate when dealing with Gaussian Mixture Model (GMM). When the sample size is smaller than the data dimension, this could lead…
We consider a cell-free Massive multiple-input multiple-output (MIMO) system and investigate the system performance for the case when the quantized version of the estimated channel and the quantized received signal are available at the…
We consider zero-forcing equalization of frequency selective MIMO channels by causal and linear time-invariant precoders in the presence of intersymbol interference. Our motivation is twofold. First, we are concerned with the optimal…
The high hardware complexity of a massive MIMO base station, which requires hundreds of radio chains, makes it challenging to build commercially. One way to reduce the hardware complexity and power consumption of the receiver is to lower…
Low-resolution analog-to-digital converters (ADCs) have emerged as a promising technology for reducing power consumption and complexity in massive multiple-input multiple-output (MIMO) systems while maintaining satisfactory spectral and…
This paper analyzes the performance of multicell massive multiple-input and multiple-output (MIMO) systems with variable-resolution analog-to-digital converters (ADCs). In such an architecture, each ADC uses arbitrary quantization…
Signal processing in wireless communications, such as precoding, detection, and channel estimation, are basically about solving inverse matrix problems, which, however, are slow and inefficient in conventional digital computers, thus…
As communication systems advance towards the future 6G era, the incorporation of large-scale antenna arrays in base stations (BSs) presents challenges such as increased hardware costs and energy consumption. To address these issues, the use…
Cell-free massive MIMO (CF-mMIMO) is expected to provide reliable wireless services for a large number of user equipments (UEs) using access points (APs) distributed across a wide area. When the UEs are battery-powered, uplink energy…