相关论文: Beam Training and Allocation for Multiuser Millime…

Channel knowledge map (CKM) emerges as a promising framework to acquire location-specific channel information without consuming wireless resources, creating new horizons for advanced wireless network design and optimization. Despite its…

In this paper, a joint task, spectrum, and transmit power allocation problem is investigated for a wireless network in which the base stations (BSs) are equipped with mobile edge computing (MEC) servers to jointly provide computational and…

Massive multiple-input multiple-output (mMIMO) communications are one of the enabling technologies of 5G and beyond networks. While prior work indicates that mMIMO networks employing time division duplexing have a significant capacity…

Reconfigurable holographic surfaces (RHSs) have been suggested as an energy-efficient solution for extremely large-scale arrays. By controlling the amplitude of RHS elements, high-gain directional holographic patterns can be achieved.…

Extremely large-scale reconfigurable intelligent surface (XL-RIS) can effectively overcome severe fading and provide higher communication performance. However, current research on XL-RIS overlooks the discrete phase-shift characteristics of…

In this paper, the problem of pilot beam pattern design for channel estimation in massive multiple-input multiple-output systems with a large number of transmit antennas at the base station is considered, and a new algorithm for pilot beam…

Beam training based on hierarchical codebook for millimeter wave (mmWave) massive MIMO is investigated. Unlike the existing work using the same hierarchical codebook to estimate different multi-path components (MPCs), dynamic hierarchical…

This paper explores the integration of reconfigurable intelligent surfaces (RISs) into cell-free massive multiple-input-multiple-output (CF-mMIMO) networks operating in FR1 and FR3 frequency bands. We present a comprehensive framework for…

In this paper, we study efficient multi-beam training design for near-field communications to reduce the beam training overhead of conventional single-beam training methods. In particular, the array-division based multi-beam training…

In this paper, we investigate a multiple-input multiple-output (MIMO) integrated sensing and communication (ISAC) system under typical block-fading channels. As a non-trivial extension to most existing works on ISAC, both the training and…

Multi-user millimeter-wave communication relies on narrow beams and dense cell deployments to ensure reliable connectivity. However, tracking optimal beams for multiple mobile users across multiple base stations (BSs) results in significant…

The focus of this paper is on multi-user MIMO transmissions for millimeter wave systems with a hybrid precoding architecture at the base-station. To enable multi-user transmissions, the base-station uses a cell-specific codebook of…

Intelligent reflecting surface (IRS) is an emerging technology to enhance the spectral and energy efficiency of wireless communications cost-effectively. This letter considers a new multi-IRS aided wireless network where a cascaded…

Large number of antennas and radio frequency (RF) chains at the base stations (BSs) lead to high energy consumption in massive MIMO systems. Thus, how to improve the energy efficiency (EE) with a computationally efficient approach is a…

Channel estimation in the RIS-aided massive multiuser multiple-input single-output (MU-MISO) wireless communication systems is challenging due to the passive feature of RIS and the large number of reflecting elements that incur high channel…

Intelligent reflecting surface (IRS) is envisioned to play a significant role in future wireless communication systems thanks to its powerful capability of enabling smart and reconfigurable radio environment. In this paper, we study the…

This article investigates beam alignment for multi-user millimeter wave (mmWave) massive multi-input multi-output system. Unlike the existing works using machine learning (ML), an alignment method with partial beams using ML (AMPBML) is…

Radio Resource Management is a challenging topic in future 6G networks where novel applications create strong competition among the users for the available resources. In this work we consider the frequency scheduling problem in a multi-user…

Massive MIMO is a variant of multiuser MIMO in which the number of antennas at the base station (BS) $M$ is very large and typically much larger than the number of served users (data streams) $K$. Recent research has illustrated the…

In this paper, beam training and beam tracking are investigated for extremely large-scale multiple-input-multiple-output communication systems with partially-connected hybrid combining structures. Firstly, we propose a two-stage…