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This paper explores the integration of Open Radio Access Network (O-RAN) principles with non-terrestrial networks (NTN) and investigates the optimization of the functional split between Centralized Units (CU) and Distributed Units (DU) to…
In this paper, we study the joint resource allocation algorithm design for downlink and uplink multicarrier transmission assisted by a shared user equipment (UE)-side distributed antenna system (SUDAS). The proposed SUDAS simultaneously…
Reliable downlink communication in satellite-to-underground networks remains challenging due to severe signal attenuation caused by underground soil and refraction in the air-soil interface. To address this, we propose a novel cooperative…
Deep neural networks (DNNs) have been introduced for designing wireless policies by approximating the mappings from environmental parameters to solutions of optimization problems. Considering that labeled training samples are hard to…
The 5th-generation wireless networks (5G) technologies and mobile edge computing (MEC) provide great promises of enabling new capabilities for the industrial Internet of Things. However, the solutions enabled by the 5G ultra-reliable…
This paper considers wireless uplink information and downlink power transfer in cell-free massive multiple-input multiple-output systems. The single-antenna user equipments (UEs) utilize the energy harvested in the downlink to transmit…
This paper proposes a unified semi-blind detection framework for sourced and unsourced random access (RA), which enables next-generation ultra-reliable low-latency communications (URLLC) with massive devices. Specifically, the active…
The recent advance in radio-frequency (RF) wireless energy transfer (WET) has motivated the study of wireless powered communication network (WPCN), in which distributed wireless devices are powered via dedicated WET by the hybrid…
In this paper, the problem of uplink (UL) and downlink (DL) resource optimization, mode selection and power allocation is studied for wireless cellular networks under the assumption of in-band full duplex (IBFD) base stations,…
With the rapid increase in demand for mobile data, mobile network operators are trying to expand wireless network capacity by deploying wireless local area network (LAN) hotspots on to which they can offload their mobile traffic. However,…
Applications of intelligent reflecting surfaces (IRSs) in wireless networks have attracted significant attention recently. Most of the relevant literature is focused on the single cell setting where a single IRS is deployed and perfect…
In the future 6th generation networks, ultra-reliable and low-latency communications (URLLC) will lay the foundation for emerging mission-critical applications that have stringent requirements on end-to-end delay and reliability. Existing…
With the rapid deployment of the Internet of Things (IoT), fifth-generation (5G) and beyond 5G networks are required to support massive access of a huge number of devices over limited radio spectrum radio. In wireless networks, different…
In this paper, a novel experienced deep reinforcement learning (deep-RL) framework is proposed to provide model-free resource allocation for ultra reliable low latency communication (URLLC). The proposed, experienced deep-RL framework can…
In this paper, we employ deep reinforcement learning to develop a novel radio resource allocation and packet scheduling scheme for different Quality of Service (QoS) requirements applicable to LTEadvanced and 5G networks. In addition,…
Unmanned aerial vehicles (UAVs) are the emerging vital components of millimeter wave (mmWave) wireless systems. Accurate beam alignment is essential for efficient beam-based mmWave communications of UAVs with base stations (BSs).…
With the explosive growth in mobile data traffic, ultra-dense network (UDN) where a large number of small cells are densely deployed on top of macro cells has received a great deal of attention in recent years. While UDN offers a number of…
Device-to-device (D2D) technology enables direct communication between adjacent devices within cellular networks. Due to its high data rate, low latency, and performance improvement in spectrum and energy efficiency, it has been widely…
The mode selection and resource allocation in fog radio access networks (F-RANs) have been advocated as key techniques to improve spectral and energy efficiency. In this paper, we investigate the joint optimization of mode selection and…
To decrease the training overhead and improve the channel estimation accuracy in uplink cloud radio access networks (C-RANs), a superimposed-segment training design is proposed. The core idea of the proposal is that each mobile station…