相关论文: Joint Unicast and Multi-group Multicast Transmissi…
For MIMO systems, due to the deployment of multiple antennas at both the transmitter and the receiver, the design variables e.g., precoders, equalizers, training sequences, etc. are usually matrices. It is well known that matrix operations…
This paper tackles the problem of downlink data transmission in massive multiple-input multiple-output (MIMO) systems where user equipments (UEs) exhibit high spatial correlation and channel estimation is limited by strong pilot…
Consider media streaming in MIMO interference networks whereby multiple base stations (BS) simultaneously deliver media to their associated users using fixed data rates. The performance is fundamentally limited by the cross-link…
This paper studies a multiple-input multiple-output (MIMO) integrated sensing and communication (ISAC) system, in which a multi-antenna base station (BS) sends unified wireless signals to estimate an extended target and communicate with a…
Cell-free (CF) massive multiple-input multiple-output (MIMO) systems are expected to implement advanced cooperative communication techniques to let geographically distributed access points jointly serve user equipments. Building on the…
This paper presents a novel massive multiple-input multiple-output (MIMO) transmission in beam domain for optical wireless communications. The optical base station equipped with massive optical transmitters communicates with a number of…
In this work, performance of a multi-antenna multiuser unmanned aerial vehicle (UAV) assisted terrestrial-satellite communication system over mixed free space optics (FSO)/ radio frequency (RF) channels is analyzed. Downlink transmission…
For a multi-user interference channel with multi-antenna transmitters and single-antenna receivers, by restricting each transmitter to Gaussian input and each receiver to a single-user detector, computing the largest achievable rate region…
Imagine a coverage area where each mobile device is communicating with a preferred set of wireless access points (among many) that are selected based on its needs and cooperate to jointly serve it, instead of creating autonomous cells. This…
Pareto front profiling in multi-objective optimization (MOO), i.e., finding a diverse set of Pareto optimal solutions, is challenging, especially with expensive objectives that require training a neural network. Typically, in MOO for neural…
The evolution of gene regulatory networks in variable environments poses Multi-objective Optimization Problem (MOP), where the expression levels of genes must be tuned to meet the demands of each environment. When formalized in the context…
In this paper, we investigate power efficient resource allocation algorithm design for multiuser wireless communication systems employing a full-duplex (FD) radio base station for serving multiple half-duplex (HD) downlink and uplink users…
Wireless power transfer (WPT) is a promising new solution to provide convenient and perpetual energy supplies to wireless networks. In practice, WPT is implementable by various technologies such as inductive coupling, magnetic resonate…
In contrast to Part I of this treatise [1] that focuses on the optimization problems associated with single matrix variables, in this paper, we investigate the application of the matrix-monotonic optimization framework in the optimization…
Conventional multiple-input multiple-output (MIMO) systems mainly rely on fixed antenna arrays, which limits their capability to adapt the effective channel matrix to the propagation environment. Rotatable antennas (RAs), which enable…
This paper investigates wireless information and power transfer in a full-duplex MIMO relay channel where the self-sustained relay harvests energy from both source transmit signal and self-interference signal to decode and forward source…
We study a multiple-input multiple-output (MIMO) multiple access channel (MAC) from several multi-antenna transmitters to a multi-antenna receiver. The fading channels between the transmitters and the receiver are modeled by random…
In this paper, we investigate high-altitude platform station (HAPS) wireless networks for simultaneous non-orthogonal unicast and multicast transmissions. Specifically, stacked intelligent metasurface (SIM)-based wave-domain beamforming is…
Multiple-objective optimization (MOO) aims to simultaneously optimize multiple conflicting objectives and has found important applications in machine learning, such as minimizing classification loss and discrepancy in treating different…
This paper deals with the problem of precoding in multibeam satellite systems. In contrast to general multiuser multiple-input-multiple-output (MIMO) cellular schemes, multibeam satellite architectures suffer from different challenges.…