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This papera 1 investigates deep reinforcement learning (DRL) based on a Recurrent Neural Network (RNN) for Dynamic Spectrum Access (DSA) under partial observations, referred to as a Deep Recurrent Q-Network (DRQN). Specifically, we consider a scenario with multiple independent channels and multiple heterogeneous Primary Users (PUs). Two key challenges in our problem formulation are that we assume our

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This paper develops a stochastic geometry-based approach for the modeling, analysis, and optimization of wireless cloud caching networks comprised of multiple-antenna radio units (RUs) inside clouds with coordinated multi-point transmissions and guard zones. We consider Poisson cluster processes to model RUs and users, and the probabilistic content placement to cache files in RUs. Accordingly, we study

The combination of recent emerging technologies such as network function virtualization (NFV) and network programmability (SDN) gave birth to the novel Network Slicing paradigm. 5G networks consist of multi-tenant infrastructures capable of offering leased network “slices” to new customers (e.g., vertical industries) enabling a new telecom business model: Slice-as-a-Service (SlaaS). However, as the

In this paper, visible light-based positioning (VLP) is studied. VLP is greatly challenging because (i) it is essentially a non-convex optimization problem since the visible-light received signal strength (RSS) is nonlinear with the user equipment (UE) position; and (ii) in addition to the UE location, the visible light RSS also depends on the UE orientation and small-scale channel gains, which are

The ever-increasing demand for media streaming together with limited backhaul capacity renders developing efficient file-delivery methods imperative. One such method is femto-caching, which, despite its great potential, imposes several challenges such as efficient resource management. We study a resource allocation problem for joint caching and transmission in small cell networks, where the system

This paper investigates the rotary-wing unmanned aerial vehicle (UAV)-enabled full-duplex wireless-powered Internet-of-Things (IoT) networks, in which a rotary-wing UAV equipped with a full-duplex hybrid access point (HAP) serves multiple sparsely-distributed energy-constrained IoT sensors. The UAV broadcasts energy when flying and hovering, and collects information only when hovering. It is assumed

Non-orthogonal multiple access (NOMA) and mobile edge computing (MEC) have been recognized as promising technologies for the beyond fifth generation networks to achieve significant capacity improvement and delay reduction. In this paper, the technologies of hybrid NOMA and MEC are integrated. In the hybrid NOMA MEC system, multiple users are classified into different groups and each group is allocated

In this paper, we characterize the performance of several canonical mobility models in a drone cellular network in which drone base stations (DBSs) serve a set of user equipment (UE) on the ground. In particular, we consider the following four mobility models: (i) straight line (SL), (ii) random stop (RS), (iii) random walk (RW), and (iv) random waypoint (RWP), among which the SL mobility model is

Incentive mechanisms have been commonly proposed to encourage people to participate in mobile crowdsensing (MCS). However, most of them set unchangeable rewards for sensing tasks, while the inherent inequality and on-demand feature of sensing tasks have been long ignored, especially for location-dependent sensing tasks (LDSTs). In this paper, we focus on location-dependent MCS systems and propose a

Drones can be used for many assistance roles in complex communication scenarios and play as the aerial relays to support terrestrial communications. Although a great deal of emphasis has been placed on the drone-assisted networks, existing work focuses on routing protocols without fully exploiting the drones superiority and flexibility. To fill this gap, this paper proposes a collaborative communication

Reliable group video call is one of the main services offered by future Mission-Critical Communications (MCC). To support its requirements, coordinated multi-point transmission in multi-cell environments is an attractive feature for MCC over Multimedia Broadcast Multicast Services owing to its potential for coverage improvement and multicast transmission. In such a scheme, full cooperation among all

In mobile edge computing (MEC) systems, edge service caching refers to pre-storing the necessary programs for executing computation tasks at MEC servers. Service caching effectively reduces the real-time delay/bandwidth cost on acquiring and initializing service applications when computation tasks are offloaded to the MEC servers. The limited caching space at resource-constrained edge servers calls

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Pointing and acquisition are an important aspect of free-space optical communications because of the narrow beamwidth associated with the optical signal. In this paper, we have analyzed the pointing and acquisition problem in free-space optical communications for photon-counting detector arrays and Gaussian beams. In this regard, we have considered the maximum likelihood detection for detecting the

The field trial results for massive multi-user multiple-input multiple-output (MU-MIMO) transmission at 28 GHz with 500 MHz bandwidth are reported in this paper. In this experiment, hybrid beamforming with block diagonal precoding is employed, in which channel state information is acquired by uplink sounding assuming channel reciprocity in a time division duplex system. 8-user MU-MIMO scenarios with

Non-orthogonal multiple access (NOMA) will provide massive connectivity for future Internet of Things. However, the intrinsic non-orthogonality in NOMA makes it non-trivial to approach the performance limit with only conventional communication-theoretic tools. In this paper, we resort to deep multi-task learning for end-to-end optimization of NOMA, by regarding the overlapped transmissions as multiple

The autonomous underwater vehicle(AUV)-aided localization techniques for underwater acoustic devices show promising applications in many scenarios, and most researches in this area are based on the time of arrival (ToA) or the time difference of arrival (TDoA) measurements. However, these measurements are not readily available. To develop a more universally applicable scheme, we investigate the possibility

Wireless content caching has recently been considered as an efficient way in fog radio access networks (F-RANs) to alleviate the heavy burden on capacity-limited fronthaul links and reduce delivery latency. In this paper, an advanced minimal delay association policy is proposed to minimize latency while guaranteeing spectral efficiency in F-RANs. By utilizing stochastic geometry and queueing theory

Massive numbers of nodes will be connected in future wireless networks. This brings great difficulty to collect a large amount of data. Instead of collecting the data individually, computation over multi-access channels (CoMAC) provides an intelligent solution by computing a desired function over the air based on the signal-superposition property of wireless channels. To improve the spectrum efficiency

In this paper, we investigate the problem of age of information (AoI)-aware radio resource management for expected long-term performance optimization in a Manhattan grid vehicle-to-vehicle network. With the observation of global network state at each scheduling slot, the roadside unit (RSU) allocates the frequency bands and schedules packet transmissions for all vehicle user equipment-pairs (VUE-pairs)

In this paper, we analyze vertical handovers in heterogeneous networks. Vertical handovers are an important ramification of user mobility in a heterogeneous wireless network since they directly impact network performance, such as throughput, packet delay, or call blocking probability. However, the study of vertical handovers faces many difficulties when it comes to analysis, including network modeling

One fundamental challenge in 5G URLLC is how to optimize massive MIMO systems for achieving low latency and high reliability. A natural design choice to maximize reliability and minimize retransmission is to select the lowest allowed target error rate. However, the overall latency is the sum of queueing latency and retransmission latency, hence choosing the lowest target error rate does not always

Power allocation plays a vital role in coordinating interference between Device-to-Device (D2D) and cellular communications, and when power allocation meets simultaneous wireless information and power transfer (SWIPT), the energy efficiency of D2D communications can be significantly improved. While numerous research studies have been conducted on D2D power allocation, most of these studies do not take

Despite the widespread popularity of stochastic geometry analysis for cellular networks, most analytical results lack the perspective of channel-adaptive user scheduling. This study presents a stochastic geometry analysis of the SINR distribution and scheduling gain of normalized SNR-based scheduling in an uplink Poisson cellular network, in which the per-user truncated fractional transmit power control

Consider an uplink cloud radio access network where users are observed simultaneously by several base stations, each with a rate-limited link to a central processor, which wishes to decode all transmitted messages. Recent efforts have demonstrated the advantages of compression-based strategies that send quantized channel observations to the central processor, rather than attempt local decoding. We

Peak to average power ratio (PAPR) reduction of OFDM signals has extensively been studied in the literature. Tone Reservation (TR) is one of the most famous algorithms and has already been included in some digital television standards such as DVB-T2 and ASTC3.0. However, the literature is still lacking theoretical analysis and performance bounds for the PAPR reduction of OFDM signals, especially using

In order to cope with the explosive growth of mobile traffic, many traffic offloading schemes such as heterogenous networks have been developed to enhance network capacity of the Radio Access Network (RAN). Among them, networking of Low-Earth Orbit (LEO) satellites promises to significantly improve the RAN performance due to its economical prospect and advantages in high bandwidth and low latency.

Mobile edge computing (MEC) has been identified as a key technique of next-generation wireless networks, which supports cloud computing along with other compelling service capabilities at the network’s edge with the objective of reducing the system delay. As one of the prospective candidates for new spectrum in next-generation networks, millimeter wave (mmWave) communications has been gaining significant

In this paper, we propose a low-complexity user selection algorithm for an uplink multiuser transmission in millimeter wave (mmWave) WLAN. We first formulate the user selection problem, taking hybrid beamforming (HBF), an NP-hard problem, into consideration. We then develop a three-step HBF algorithm that incorporates user selection. Specifically, users can be selected based on semi-orthogonality instead

Providing reliable and efficient coverage for cell-edge mobile users (MUs) is a key issue in wireless communication networks. With non-uniform structure and heterogeneity of network topology in the 5G/B5G networks, performance improvement of cell-edge MUs becomes even more challenging. Unmanned aerial vehicle (UAV) exhibits a comparable advantage in enhancing cell edge performance due to its flexible

The use of low-resolution analog-to-digital converters (ADCs) is considered to be an effective technique to reduce the power consumption and hardware complexity of wireless transceivers. However, in systems with low-resolution ADCs, obtaining channel state information (CSI) is difficult due to significant distortions in the received signals. The primary motivation of this paper is to show that learning

This paper studies a single-user wireless powered mobile edge computing (MEC) system, in which one multi-antenna energy transmitter (ET) employs energy beamforming for wireless power transfer (WPT) towards the user, and the user relies on the harvested energy to locally execute a portion of tasks and offload the other portion to an access point (AP) integrated with an MEC server for remote execution

Self-interference (SI) cancellation for full-duplex (FD) multiple input multiple output (MIMO) systems is challenging due to both hardware and signal processing complexity. In this paper, a beam-based adaptive filter structure with analog least mean square (ALMS) loops is proposed to significantly reduce the complexity of SI cancellation for FD MIMO systems. With this structure, the number of adaptive

Standard blind interference alignment (sBIA) suffers from noise accumulation which severely deteriorates received signal-to-noise ratio (SNR) and significantly reduces transmission rate. A noise accumulation factor is proposed to describe the loss between the user’s received SNR, and the final post processing SNR which determines the performance of the decoding of the encoded data streams (EDSs). A

In this paper, we propose an enhanced Huffman coded orthogonal frequency-division multiplexing with index modulation (EHC-OFDM-IM) scheme. The proposed scheme is capable of utilizing all legitimate subcarrier activation patterns (SAPs) and adapting the bijective mapping relation between SAPs and leaves on a given Huffman tree according to channel state information (CSI). As a result, a dynamic codebook

5G millimeter-wave (mmW) systems rely on electronically steerable antenna arrays to support directional communications. Directionality complicates the initial access (IA) process, whereby a base station (BS) announces itself to nearby user equipments (UEs), giving them the opportunity to associate with this BS. Existing approaches for IA suffer from long discovery time and/or nonnegligable probability

To meet the wide range of 5G use cases in a cost-efficient way, network slicing has been advocated as a key enabler. Unlike the core network slicing in a virtualized environment, radio access network (RAN) slicing is still in its infancy and the corresponding realization is challenging. In this paper, we investigate the realization approach of fog RAN slicing, where two network slice instances for

Direct communication among user equipments, called Device-to-Device (D2D) communication, is envisioned in academia and industry to enhance future cellular networks for increased spectral efficiency. Mode selection considers the question which links should be offloaded to use direct communication mode and is one of the core questions in D2D research. In this work, we ask the question which information

In a wiretap channel, due to the passive nature of eavesdropper and the inevitable errors during channel estimation or feedback, the channel state information is usually imperfectly known at the transmitter. While probabilistic constrained secure transmission provides an elegant formulation to tackle these uncertainties, current works mostly focus on the fixed-rate secure transmission design. To exploit

We consider a block fading additive white Gaussian noise (AWGN) channel with perfect channel state information (CSI) at the transmitter (CSIT) and the receiver (CSIR). For a given codeword length and non-vanishing average probability of error, we obtain lower and upper bounds on the maximum transmission rate. First, we derive bounds when the transmitter has a time varying peak power constraint imposed

This paper investigates learning-based caching in small-cell networks (SCNs) when user preference is unknown. The goal is to optimize the cache placement in each small base station (SBS) for minimizing the system long-term transmission delay. We model this sequential multi-agent decision making problem in a multi-agent multi-armed bandit (MAMAB) perspective. Rather than estimating user preference first