Related papers: Optimum GSSK Transmission in Massive MIMO Systems …
This work focuses on a large-scale multi-cell multi-user MIMO system in which $L$ base stations (BSs) of $N$ antennas each communicate with $K$ single-antenna user equipments. We consider the design of the linear precoder that minimizes the…
For next-generation green communication systems, this article proposes an innovative communication system based on frequency-diverse array-multiple-input multiple-output (FDA-MIMO) technology, which aims to achieve high data rates while…
Integrated sensing and communications (ISAC) is envisioned as a key feature in future wireless communications networks. Its integration with massive multiple-input-multiple-output (MIMO) techniques promises to leverage substantial spatial…
We present novel soft-input soft-output (SISO) multiple-input multiple-output (MIMO) detectors based on the Chase detection principle [1] in the context of iterative and decoding (IDD). The proposed detector complexity is linear in the…
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…
In this paper, we consider a multiuser massive single-input multiple-output (SIMO) enabled Industrial Internet of Things (IIoT) communication system. To reduce the latency and overhead caused by channel estimation, we assume that only the…
Multiple-input multiple-output (MIMO) has been a key technology of wireless communications for decades. A typical MIMO system employs antenna arrays with the inter-antenna spacing being half of the signal wavelength, which we term as…
Massive MIMO, a candidate for 5G technology, promises significant gains in wireless data rates and link reliability by using large numbers of antennas (more than 64) at the base transceiver station (BTS). Extra antennas help by focusing the…
A novel compressive-sensing based signal multiplexing scheme is proposed in this paper to further improve the multiplexing gain for multiple input multiple output (MIMO) system. At the transmitter side, a Gaussian random measurement matrix…
In this study, we revisit the performance analysis of distributed beamforming architectures in dense user-centric cell-free massive multiple-input multiple-output (mMIMO) systems in line-of-sight (LoS) scenarios. By incorporating a recently…
A large-scale MIMO (multiple-input multiple-output) system offers significant advantages in wireless communication, including potential spatial multiplexing and beamforming capabilities. However, channel estimation becomes challenging with…
This work proposes a global navigation satellite system (GNSS) spoofing detection and classification technique for single antenna receivers. We formulate an optimization problem at the baseband correlator domain by using the Least Absolute…
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 study how coded caching can be efficiently applied to multiple-input multiple-output (MIMO) communications. This is an extension to cache-aided multiple-input single-output (MISO) communications, where it is shown that…
This paper proposes the class of Generalized Least-Square-Error (GLSE) precoders for multiuser massive MIMO systems. For a generic transmit constellation, GLSE precoders minimize the interference at user terminals assuring that given…
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…
This paper addresses the problem of estimating sparse channels in massive MIMO-OFDM systems. Most wireless channels are sparse in nature with large delay spread. In addition, these channels as observed by multiple antennas in a neighborhood…
Communication-efficient distributed training algorithms have received considerable interest recently due to their benefits for training Large Language Models (LLMs) in bandwidth-constrained settings, such as across datacenters and over the…
Millimeter wave multiple-input multiple-output (MIMO) communication systems must operate over sparse wireless links and will require large antenna arrays to provide high throughput. To achieve sufficient array gains, these systems must…
Compressive subspace learning (CSL) with the exploitation of space diversity has found a potential performance improvement for wideband spectrum sensing (WBSS). However, previous works mainly focus on either exploiting antenna…