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Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers.

Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.

Presents the table of contents for this issue of the publication.

Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.

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Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers.

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Presents the table of contents for this issue of the publication.

Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.

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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In this paper, we propose the hybrid-precoding design that alleviates the performance loss caused by beam-misalignment in the mmWave multi-user communication systems. To this end, we firstly design the beam-misalignment aware fully-digital precoders for two distinct scenarios. First, for a base-station (BS) with full estimated channel-state-information (CSI), the minimum-mean-squared-error metric incorporating

A massive MIMO network can serve ten’s of users simultaneously. However, in dense scenarios the users are potentially closely-spaced, potentially resulting in substantial inter-user interference. Scheduling can overcome this by selecting the users that lead to the highest combined spectral efficiency. As scheduling comes with a significant pilot overhead, an alternative strategy could minimize user

In order to improve the transmission reliability in current wireless communication systems, the Hybrid Automatic ReQuest (HARQ) protocol is employed to manage the unknown time-varying channel. The acknowledgments are fed back with delay on the return link. To fill up the idle time between a transmission and its acknowledgment, parallel HARQ streams associated with different messages are carried out

Unmanned aerial vehicles (UAVs) have been applied in many different communication scenarios due to their mobility and manipuility. In this paper, we investigate a UAV-aided relay network, where a number of ground users in the urban area with many obstructions need to collect data from a base station (BS), and a UAV could fly around above the users and serve as a decode-and-forward (DF) mobile relay

Edge computing (EC) is an emerging paradigm to push sufficient computation resources towards the network edge, improving application performance significantly by offloading applications to the edge computing node. We investigate continuous application offloading decision in EC, for which it is uncertain how users operate continuous applications and how long continuous applications last before completion

The massive sensing data generated by Internet-of-Things will provide fuel for ubiquitous artificial intelligence (AI), automating the operations of our society ranging from transportation to healthcare. The implementation of ubiquitous AI, however, entails labelling of an enormous amount of data prior to the training of AI models via supervised learning. To tackle this challenge, we explore a new

This paper investigates the capacity region and detailed characterizations of capacity-achieving signaling schemes of a multiple access channel (MAC) with two users communicating to a base station (BS) equipped with 1-bit quantizers. We consider Rayleigh fading channels where channel state information (CSI) is known only at BS. Towards this end, we first study the weighted sum-rate maximization problem

We consider a cellular network deployment where UAV-to-UAV (U2U) transmit-receive pairs share the same spectrum with the uplink (UL) of cellular ground users (GUEs). For this setup, we focus on analyzing and comparing the performance of two spectrum sharing mechanisms: (i) underlay, where the same time-frequency resources may be accessed by both UAVs and GUEs, resulting in mutual interference, and

We consider the non-coherent single-input multiple-output (SIMO) multiple access channel with general signaling under spatially correlated Rayleigh block fading. We propose a novel soft-output multi-user detector that computes an approximate marginal posterior of each transmitted signal using only the knowledge about the channel distribution. Our detector is based on expectation propagation (EP) approximate

This paper designs a novel opportunistic adaptive non-orthogonal multiple access (OA-NOMA) strategy, where a base station (BS) employs NOMA to serve a near user (NU)-far user (FU) pair opportunistically scheduled from $M$ NUs and $K$ FUs. In particular, the NOMA transmission to the scheduled NU-FU pair adaptively operates in one of two modes: Direct NOMA mode , in which the BS directly serves the scheduled

This paper addresses multi-user multi-cluster massive multiple-input-multiple-output (MIMO) systems with non-orthogonal multiple access (NOMA). Assuming the downlink mode, and taking into consideration the impact of imperfect successive interference cancellation (SIC), an in-depth analytical analysis is carried out, in which closed-form expressions for the outage probability and ergodic rates are derived

Accurate wireless positioning of mobile agents is challenging in non-line-of-sight (NLOS) propagation environments due to unknown range or angle biases. In this paper, we develop a cooperative localization algorithm for mixed line-of-sight (LOS)/NLOS environments where the NLOS effect is mitigated by exploiting the geometric relationship of the range biases. In particular, we cast the localization

Mobile edge computing (MEC), as a promising technology, provides proximate and prompt computing service for mobile users on various applications. With appropriate incentives, profit-driven users can offload multi-task requests across heterogeneous edge servers. However, such incentive trade lacks a trustworthy platform. Due to the decentralized nature of MEC, trading information from players is easily

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Radio frequency (RF) energy harvesting is key in attaining perpetual lifetime for time-critical wireless powered communication networks (WPCNs) due to full control on energy transfer, far field region, small and low-cost circuitry. In this paper, we propose a novel minimum length scheduling problem to determine the optimal power control, time allocation and schedule subject to data, energy causality

Ambient radio frequency (RF) energy harvesting technology provides a hopeful solution to power the low-power electronic system. Nevertheless, the extremely low power density and randomness of ambient RF energy pose a significant obstacle to the application of ambient RF energy harvesting technology. Aiming at wireless transmission by ambient RF-powered sensors, this paper presents a cooperative communication

Recently, discontinuous reception mechanisms (DRX) and wake-up schemes (WuS) have been proposed to enhance the energy efficiency of 5G mobile devices and prolong the battery lifetime. The existing DRX and WuS use commonly pre-configured parameters that cannot be adjusted dynamically. In this paper, a novel wake-up scheduling (WuSched) concept is introduced to further improve the energy efficiency of

Direct-conversion receivers (DCRs) have been adopted in wideband communication systems owing to their simple structure and low cost, however, their operation is affected by amplitude and phase mismatches between their analog inphase (I) and quadrature (Q) branches, as well as the discrepancy of low-pass filter coefficients between these two channels. In this paper, a blind adaptive frequency-dependent

A reliable vehicle-to-vehicle (V2V) channel model is necessary for intelligent transportation systems (ITSs) design. Due to the high mobility of vehicles and the low heights of antennas, the line-of-sight (LOS) propagation paths in V2V communications are more likely to be obstructed by large vehicles such as buses. Therefore, it is worthwhile to conduct in-depth investigations on obstructed line-of

In this paper, we propose a novel multi-slot pilot allocation (MSPA) random access scheme with unequal access latency (UAL) protection for user equipments (UEs) in massive machine-type communications (mMTC). In order to provide UAL protection, we allocate the UEs into different groups according to their UAL requirements, where the higher priority groups can access in a stringent latency under the required

Due to the continuous demand for higher bit rates, the management of the spatio-temporal intersymbol interference in frequency-selective multiple-input multiple-output (MIMO) channels becomes increasingly important. For single-input single-output channels, equalized precoded partial-response signaling is capable of handling a large amount of intersymbol interference, but, to date, no equalization scheme

We consider a joint radar parameter estimation and communication system using orthogonal time frequency space (OTFS) modulation. The scenario is motivated by vehicular applications where a vehicle (or the infrastructure) equipped with a mono-static radar wishes to communicate data to its target receiver, while estimating parameters of interest related to this receiver. Provided that the radar-equipped

Wireless underground sensor networks (WUSNs) are becoming ubiquitous in many areas. The design of robust systems requires an extensive understanding of the underground (UG) channel characteristics. In this article, the UG channel impulse response is modeled and validated via extensive experiments in indoor and field testbed settings. Three distinct types of soils are selected with sand contents ranging

Due to recent advances in laser satellite communications technology, free-space optical (FSO) links are presented as an ideal alternative to the conventional radio frequency (RF) feeder links of the geostationary satellite for next generation very high throughput satellite (VHTS) systems. In this paper, we investigate the performance of multibeam VHTS systems that account for nonlinear high power amplifiers

Recent years have witnessed the rapid proliferation of backscatter technologies that realize the ubiquitous and long-term connectivity to empower smart cities and smart homes. Localizing such backscatter tags is crucial for IoT-based smart applications. However, current backscatter localization systems require prior knowledge of the site, either a map or landmarks with known positions, which is laborious

This paper presents robust localization algorithms that use range measurements to estimate the location parameters. The non-line-of-sight (NLOS) propagation of a signal can severely deteriorate the estimation performance in indoor and population-dense urban areas. Therefore, the robust localization algorithms are considered in this paper. In particular, the robust statistics-based localization is dealt

Unreliable fading wireless channels are the main challenge for strict performance guarantees in mobile communications. Diversity schemes including massive number of antennas, huge spectrum bands and multi-connectivity links are applied to improve the outage performance. The success of these approaches relies heavily on the joint distribution of the underlying fading channels. In this work, we consider

Optical orthogonal frequency division multiplexing (O-OFDM) schemes are variations of OFDM schemes that produce non-negative signals. Asymmetrically-clipped O-OFDM (ACO-OFDM) is a single-layer O-OFDM scheme, whose spectral efficiency can be enhanced by adopting multiple ACO-OFDM layers or a combination of ACO-OFDM and other O-OFDM schemes. However, since symbol detection in such enhanced ACO-OFDM (eACO-OFDM)

In this paper, we design a frame structure for unique word (UW) based transmission of multiple-input-multiple-output (MIMO) systems under doubly-dispersive wireless channel conditions. We elaborate an energy and spectral efficiency analysis of a MIMO UW-based system vs. a conventional MIMO cyclic prefix (CP)-based system. Considering the UW-based transmission for a MIMO multi-carrier, we derive its

We investigate the coordinated multi-point noncoherent joint transmission (JT) in dense small cell networks. The goal is to design beamforming vectors for macro cell and small cell base stations (BSs) such that the weighted sum rate of the system is maximized, subject to a total transmit power at individual BSs. The optimization problem is inherently nonconvex and intractable, making it difficult to

Data rewarding is a novel business model leading a new economic trend in mobile networks, in which the operators stimulate mobile users to watch ads with data rewards and ask for corresponding payments from advertisers. Yet, due to the uncertain nature of users’ preferences, it is always challenging for the advertiser to find the best choice of data rewards to attain an optimum balance between ad revenue

High power consumption and hardware cost have motivated using low-resolution analog-to-digital converters (ADCs) for practical massive multiple-input multiple-output (mMIMO) systems. In this paper, we consider a general mMIMO multi-way relaying system with a multi-level mixed-ADC architecture in which each antenna is connected to an ADC pair with an arbitrary resolution. By leveraging on Bussgang’s

Emerging healthcare radio technologies are designed to operate in the 2.4GHz industrial, scientific and medical (ISM) band. Since both standardized (Bluetooth and Wi-Fi) and non-standardized (proprietary) devices use the same frequency band, the aggregate interference may significantly affect the performance of medical wireless systems. This paper characterizes the spatiotemporal spectrum occupancy

In the analysis of large-scale wirelessly powered networks, the energy correlation is often ignored. While this leads to remarkably simple results for key performance metrics, it is typically not realistic and accurate. Considering the accuracy, tractability, and practicability tradeoffs, this paper introduces and promotes the Poisson disk process (PDP) as a model for the energized nodes that succeed

This paper considers the sum spectral efficiency (SE) optimization problem in multi-cell Massive MIMO systems with a varying number of active users. This is formulated as a joint pilot and data power control problem. Since the problem is non-convex, we first derive a novel iterative algorithm that obtains a stationary point in polynomial time. To enable real-time implementation, we also develop a deep

This paper introduces a network linear block coding framework for multi-way relaying with differential MPSK modulation. We consider a system with $K$ user terminals and $L$ relays employing a selective detect-and-forward protocol. We show that such a system can be represented as a systematic $(K+L,K)$ linear block code. This framework allows the use of linear systematic block codes as network codes

In this work, we face the issue of achieving an efficient dynamic mapping in vehicular networking scenarios, i.e., obtaining an accurate estimate of the positions and trajectories of connected vehicles in a certain area. State-of-the-art solutions are based on the periodic broadcasting of the position information of the network nodes, with an inter-transmission period set by a congestion control scheme

The scheduling of downlink video streaming in a massive multiple-input multiple-output (MIMO) network is considered in this paper, where active users arrive randomly to request video contents of a finite playback duration via their service base stations (BSs). Each video content consisting of a sequence of segments can be transmitted to the requesting users with variable video bitrates. We formulate

Traditional symbol detection algorithms either perform poorly or are impractical to implement for Massive Multiple-Input Multiple-Output (MIMO) systems. Recently, several learning-based approaches have achieved promising results on simple channel models (e.g., i.i.d. Gaussian channel coefficients), but as we show, their performance degrades on real-world channels with spatial correlation. We propose