Matrix graph signals, which are associated with two factor graphs, are ubiquitous in daily life, such as time-varying physical signals in sensor networks and rating matrices in recommendation systems. In practice, due to the row-wise and column-wise smoothness, they are modeled as bandlimited (BL) graph signals on the product of two factor graphs. In this paper, we propose a fast sampling method for BL product graph signals by minimizing the reconstruction mean squared error (MSE). First, we formulate the MSE-based sampling objective for BL signals on a product graph. Next, we simplify the greedy subproblem using matrix inversion approximation, which involves straightforward computations between the defined joint low-pass impulse responses (JLIRs). To eliminate the huge computation and storage complexity, we propose a strategy to directly compute the greedy evaluation score based on low-dimensional LIRs on two factor graphs, leveraging the property of Kronecker product. Employing this strategy, we also extend existing popular LIR-based methods to sample signals from single graphs to product graphs with low complexity. Extensive experiments on synthetic and real-world product graph signals demonstrate that our proposed method maintains superior MSE performance compared to other extended graph sampling schemes.

This paper investigates covert communication in a hybrid-functional (HF) reconfigurable intelligent surface (RIS) assisted symbiotic radio (SR) system, where each element of RIS can adaptively switch between passive reflection and covert signal modulation mode. Since covert communication fundamentally relies on low transmission power to ensure undetectability, we try to minimize the transmit power while ensuring the covert constraint, and the joint optimization of active beamforming (BF) at access point, passive BF and mode selection at HF-RIS can be formulated as a mixed-integer fractional programming (MIFP) problem. By decomposing the original problem into the continuous beamformer design and the discrete mode selection problems, we further develop a binary search-assisted alternative beamformer optimization algorithm to obtain a stable solution of the MIFP problem. Numerical results demonstrate the superiority of the adaptive RIS mode selection covert-enhanced design over existing benchmark schemes and reveal useful insights to guide RIS mode selection design for different SR paradigms.

We investigate an energy-efficient hybrid multiple access design for backscatter communication. A dynamic backscatter device scheduling and resource allocation framework is proposed, targeted at minimizing the total energy consumption. To solve the challenging optimization problem, we devise an efficient two-sided matching-based optimization algorithm to jointly optimize the device scheduling, transmit beamforming, reflecting coefficients, and time allocation. Simulation results show that in high-density Internet of Things networks, the proposed scheme achieves nearly 60% performance improvement compared to existing baseline schemes, while revealing that energy consumption achieves its local minimum with respect to the number of time slots.

ABSTRACT This paper investigates a buffer‐aided cooperative non‐orthogonal multiple access scheme for simultaneous wireless information and power transfer systems, where the near users are equipped with data and energy buffers. To improve the overall energy efficiency, the transmission mode of the considered system adaptively chooses the base station or near‐user transmission mode. Given the target quality of service and limited resources, the long‐term power consumption minimization is formulated by a mixed integer non‐linear programming problem, where the model selection, user scheduling, and power consumption are jointly optimized. To efficiently tackle such a challenging problem, we transform the original problem into an instantaneous non‐convex problem by employing the Lyapunov optimization framework. Then, using the successive convex approximation algorithms, we approximate the instantaneous non‐convex problem as a linear programming problem, where the Karush–Kuhn–Tucker solution of the power allocation can be obtained. The optimality and complexity of the proposed scheme are theoretically analyzed. The simulation results show that the proposed scheme can achieve a near‐optimal performance and significantly improves the energy efficiency compared with the conventional transmission schemes.

This paper considers the cost minimization problem in a heterogeneous mobile edge computing network, where the macro base stations are scattered over the ground to ensure the service coverage, and the small base stations are clustered around the user hotspots to improve the users’ quality of service. Specifically, the network-wide communication and computation performance are analyzed using stochastic geometry and queueing theory. Taking the obtained performance metrics as constraints, a cost minimization problem is formulated. To solve the formulated problem, we propose a globally optimal algorithm, whose optimality and complexity are theoretically analyzed. Then, to further reduce the computational complexity, the problem is reformulated as the difference of convex programming problems, which can be addressed by the concave-convex procedure. Numerical simulations verify the accuracy of the theoretical results and illustrate the superiority of the proposed algorithms.

This paper investigates covert communications in an integrated sensing and communications system, where a dual-functional base station (called Alice) covertly transmits signals to a covert user (called Bob) while sensing multiple targets, with one of them acting as a potential watcher (called Willie) and maliciously eavesdropping on legitimate communications. To shelter the covert communications, Alice transmits additional dual-functional artificial noise (DFAN) with a varying power not only to create uncertainty at Willie’s signal reception to confuse Willie but also to sense the targets simultaneously. Based on this framework, the weighted sum of the sensing beampattern means square error (MSE) and cross correlation is minimized by jointly optimizing the covert communications and DFAN signals subject to the minimum covert rate requirement. The robust design considers both cases of imperfect Willie’s CSI (WCSI) and statistical WCSI. Under the worst-case assumption that Willie can adaptively adjust the detection threshold to achieve the best detection performance, the minimum detection error probability (DEP) at Willie is analytically derived in the closed-form expression. The formulated covertness constrained optimization problems are tackled by a feasibility-checking based difference-of-convex relaxation (DC) algorithm utilizing the S-procedure, Bernstein-type inequality, and the DC method. Simulation results validate the feasibility of the proposed scheme and demonstrate the covertness performance gains achieved by our proposed design over various benchmarks.

This paper investigates a reconfigurable intelligent surface (RIS)-assisted wireless powered mobile edge computing (MEC) system, where an access point (AP) integrated with an MEC server first transmits energy signals to charge multiple energy-constrained devices in the downlink (DL), and then the devices utilize the harvested energy to perform MEC offloading in the uplink (UL) assisted by an RIS. Specifically, three multiple access protocols for MEC offloading, namely pure non-orthogonal multiple access (NOMA), pure orthogonal multiple access, and hybrid NOMA, are proposed to exploit dynamic RIS beamforming and energy recycling among devices to enhance the efficiencies of energy harvesting and MEC offloading. For each of the three protocols, a joint resource allocation framework of the AP/devices transmit power, the RIS phase shifts, and the DL/UL time allocation is formulated to minimize the energy consumption at the AP. Because of those highly coupled optimization variables, the formulated optimization problems are first shown to be non-convex, and then the intrinsic structure of the problems is exploited to devise computationally-efficient algorithms and solve them iteratively. Numverical results are provided to demonstrate the performance improvement of our proposed designs compared to various benchmark schemes, and reveal the practical significance of the considered multiple access protocols with dynamic RIS beamforming and energy recycling for spectral and energy efficient MEC offloading.

Driven by the ever-increasing requirements of ultrahigh spectral efficiency, ultralow latency, and massive connectivity, the forefront of wireless research calls for the design of advanced next-generation multiple access schemes to facilitate the provisioning of these stringent demands. This inspires the embrace of nonorthogonal multiple access (NOMA) in future wireless communication networks. Nevertheless, the support of massive access via NOMA leads to additional security threats due to the open nature of the air interface, the broadcast characteristic of radio propagation, and the intertwined relationship among paired NOMA users. To address this specific challenge, the superimposed transmission of NOMA can be explored as new opportunities for security-aware design; for example, multiuser interference inherent in NOMA can be constructively engineered to benefit communication secrecy and privacy. The purpose of this tutorial is to provide a comprehensive overview of the state-of-the-art physical layer security techniques that guarantee wireless security and privacy for NOMA networks, along with the opportunities, technical challenges, and future research trends.

This paper designs a helper-assisted offloading strategy in non-orthogonal multiple access enabled mobile edge computing systems, in order to guarantee the quality of service of the energy/delay-sensitive user equipments (UEs). To achieve a tradeoff between the energy consumption and the delay, we introduce a performance metric called energy-delay tradeoff. Aiming at the maximal energy-delay tradeoff minimization, the joint optimization of user association, resource block (RB) assignment, power allocation, task assignment, and computation resource allocation is formulated as a non-convex problem with coupled continuous and 0-1 variables. To tackle this challenging problem, we decompose it as a two-level problem. For the inner-level problem, an iterative parametric convex approximation (IPCA) algorithm is proposed. Then, based on the solution obtained from the inner-level problem, we model the outer-level problem as a four-sided matching problem, and then propose a low-complexity four-sided UE-RB-helper-server matching (FS-URHSM) algorithm. Theoretical analysis demonstrates that the IPCA algorithm can converge to a stationary Karush-Kuhn-Tucker (KKT) point and the FS-URHSM algorithm is guaranteed to converge to a stable matching with polynomial complexity. Simulation results demonstrate the superior performance of proposed algorithms in terms of the energy consumption and the delay.

This paper investigates a mobile edge computing (MEC) network assisted by an unmanned aerial vehicle (UAV), where the moving UAV and a fixed ground base station cooperatively provide MEC services for multiple ground users. To evaluate the quality of service under this architecture, we first derive the successful edge computing probability (SECP) to evaluate the service reliability. Given a target SECP requirement, we formulate a service coverage maximization problem by optimizing the UAV altitude and task offloading probability. The problem is hard to solve due to the coupled UAV altitude and task offloading probability in the derived SECP expression. To address this challenge, we first explore some interesting properties of the formulated problem, and then use these properties to develop a golden-section search based method to solve the formulated optimization problem. Numerical results are used to verify the theoretical analysis of our system and demonstrate the efficiency of the proposed scheme.

We investigate joint power allocation and decoding order selection (PA-DOS) aimed at enhancing the outage performance of non-orthogonal multiple access (NOMA) systems. By considering the diverse target rates of users, new important properties of NOMA are revealed: When users’ target rates satisfy certain conditions, the channel state information (CSI) is not required by PA-DOS to minimize the system outage probability, and different users’ outage probabilities can be minimized simultaneously; When such conditions are not satisfied, the opposite situation occurs. Following these properties, two PA-DOS strategies are designed regarding distinct user priorities, which ensure the minimization of the system outage probability and the user outage probability of the high-priority user. Especially, these strategies do not require CSI or only require one-bit CSI feedback depending on users’ target rates. Analytical and numerical results are provided to demonstrate that the proposed strategies significantly outperform the existing strategies in terms of both system and user outage performance. Furthermore, the results show that although under some target rates the minimum user outage probabilities cannot be simultaneously achieved, they can be closely approached at the same time in the high-signal-to-noise-ratio regime by the proposed strategies.

We investigate a new self-sustainable intelligent omni-surface (S-IOS) aided multi-user wireless network, where the S-IOS harvests the radio frequency energy from the signals transmitted by the access point (AP) and exploits the harvested energy to provide full-dimensional beamforming services for the users. We design a joint optimization problem of transmit beamforming at the AP, refraction/reflection beamforming at the S-IOS, and energy harvesting schedule at the S-IOS, to maximize the sum rate of the overall network. A computationally-efficient algorithm is developed to solve the problem. Numerical results demonstrate the significant importance of the S-IOS for spectral and energy efficient wireless communications.

We investigate a reconfigurable intelligent surface (RIS)-aided wireless powered mobile edge computing (MEC) network, where a new RIS-aided hybrid non-orthogonal multiple access (NOMA) offloading scheme is proposed to improve the efficiency of both MEC offloading and energy harvesting. A joint optimization framework for the transmit power, time allocation, and RIS phase shifts is developed to minimize the overall energy consumption of the network, subject to the energy causality and MEC offloading constraints. Despite of the optimization problem's non-convexity with highly coupled optimization variables, we devise a computationally-efficient algorithm to solve it iteratively. Simulation results are also provided to facilitate the performance evaluation of the RIS-aided wireless powered MEC, quantify the value of the RIS for energy efficient MEC offloading, and validate the performance gains of the proposed hybrid NOMA offloading over various baseline schemes.

Abstract With the large‐scale deployment of communication and computation units, the conventional radio access network has been gradually transformed into a sophisticated Cyber‐Physical System. Since the access network is put forward higher expectations for ultra‐reliable and low‐latency services, Short‐Packet Communications (SPC) based on Finite Blocklength Codes can be adopted to further decrease network latency and enhance communication reliability. Considering the interaction among the service provider, the network operator, and users, a three‐stage Stackelberg game is constructed to dynamically arrange communication and computation resources. In this paper, the tripartite interaction problem is modelled as a generalized Nash equilibrium problem, and the reverse induction method is employed to achieve the sub‐game equilibrium. To solve the problem of maximizing tripartite utilities, the authors propose an iterative algorithm for jointly managing resource allocation and tripartite pricing. Simulation results show that compared with the benchmark, the proposed scheme can effectively improve the utilities of users, the service provider, and the network operator and achieve a win–win situation.

Abstract This paper investigates low‐latency offloading strategy in a non‐orthogonal multiple access aided mobile edge computing (NOMA‐MEC) system consisting of K edge servers, one mobile user and one cloud server. An intelligent edge server selection strategy (IESSS) based on Markov decision process (MDP) is proposed to select an edge server, in order to reduce the task completion latency of this system. When an edge server is selected by the proposed IESSS, a joint optimization problem of power allocation and task scheduling factors is formulated to minimize the task completion latency of the hybrid NOMA‐MEC system. To solve the formulated non‐convex optimization problem with coupled variables, a low‐complexity adaptive power‐task resource allocation iterative (APTRAI) algorithm is proposed. Simulation results demonstrate the advantages of the proposed IESSS and verify the convergence and time complexity of the proposed APTRAI algorithm.

This paper investigates computing task offloading from an Internet-of-Thing (IoT) device with limited transmit power to a mobile-edge computing (MEC) server located beyond the communication range of the IoT device. We propose an opportunistic cooperative offloading (OCO) strategy that recruits the IoT device’s nearby spatially random idle-state users as helpers and opportunistically schedules one of them to partially execute the latency-critical task, and forwards the rest portion of the task to the MEC server. For the OCO strategy, we investigate the helper scheduling under three cases of system information availability, i.e., the global, partial, and distance information cases, and develop an offloading-outage optimal scheduling scheme for each case. For each scheduling scheme, an approximate expression is derived for the offloading-outage probability, with which the achieved diversity order is also theoretically evaluated. Simulation results verify our performance analysis for the OCO strategy using helper scheduling and show its achieved offloading-outage/energy consumption reduction over multi-helper cooperative offloading that fully uses all helpers for cooperation. In addition, the advantages of the proposed helper scheduling schemes over existing scheduling schemes are also demonstrated by simulations.

To enhance the outage performance of downlink non-orthogonal multiple access (NOMA) systems, we investigate opportunistic user pair scheduling (UPS) as well as the joint power allocation and decoding order selection (PA-DOS) for the scheduled user pair. Unlike most existing literature where the UPS and PA-DOS schemes are solely driven by channel conditions, we consider the impact of both the channel conditions and users’ target rates in the scheme design, since these two factors jointly determine the occurrence of transmission outages. Specifically, a two-stage rate-aware scheme for joint UPS and PA-DOS is proposed, which is proved to achieve the minimum system outage probability and guarantee fair access opportunities among users. For performance evaluation, the exact system outage probability achieved by the proposed scheme is derived in closed form, based on which a high-signal-to-noise-ratio asymptotic result is further derived for meaningful insights. Our analytical results reveal a new finding: The diversity order achieved by our proposed scheme, which is also the maximum achievable diversity order of the considered NOMA system, varies with the users’ target rates. Simulations confirm our findings and demonstrate that the proposed scheme can achieve a significant outage performance gain over the existing benchmark schemes.

This paper investigates the secure hybrid beamforming (HB) design in an intelligent reflecting surface (IRS) assisted millimeter-wave (mmWave) system, where an IRS is deployed to help the legitimate transmission from Alice to Bob under the eavesdropping of Eve. To protect the legitimate transmission, Alice employs HB to send both the information signal and the artificial noise, while the IRS employs passive beamforming (PB) to reconstruct the wireless environment. Aiming at the secrecy capacity (SC) maximization, the joint optimization of HB and PB is formulated as a non-convex problem with constant-modulus constraints. To efficiently solve such a challenging problem, the original problem is decomposed into a PB subproblem and an HB subproblem, then these subproblems are sequentially solved by the proposed algorithms. Particularly, for the PB subproblem, we propose a channel information aided PB algorithm, which is proved to converge at a stationary point. With the solution of PB subproblem, two algorithms are proposed for the HB subproblem: 1) near-optimal SC approaching HB algorithm that achieves a near-optimal solution; 2) low-complexity HB algorithm that achieves a slight lower SC with less computational complexity. Simulation results demonstrate the superior performance of proposed algorithms in comparison with the state-of-the-art works.

Abstract This paper proposes a novel multi‐phase coordinated direct and user‐assisted transmission (MP‐CDUAT) strategy for a non‐orthogonal multiple access system consisting of a base station (BS), K near users (NUs) and a far user (FU). In the first phase, the BS directly serves an opportunistically scheduled NU. For the rest phases, an NU scheduling scheme is developed to jointly select two NUs in each phase, where one receives desired message from the BS and the other one serves as a relay to help FU's receiving. To evaluate the performance of the proposed MP‐CDUAT strategy, the analytical expression of the ergodic capacity (EC) for both NU and FU is derived. With the derived results, the EC scaling of NU and FU are, respectively, derived in the high ρ regime, where the EC scaling of FU increases with the transmission phase, while the EC scaling of NU remains the same. Finally, the numerical and simulation results show that (a) our proposed strategy can improve the performance of FU without affecting the capacity scaling of served NUs; (b) the performance gain achieved by the proposed strategy is more prominent with the increasing number of the transmission phases.

Abstract With the rapid development of Internet‐of‐Things (IoT) and mobile devices, the IoT applications become more computation‐intensive and latency‐sensitive, which bring severe challenges to the resource‐limited devices. Mobile Edge Computing has served as a key promising method to enhance the network's computing capability by enabling resource‐constrained devices to offload tasks to the edge servers. A major challenge, which has been overlooked by most existing works on task offloading, is the dependencies among tasks and subtasks. In this paper, the subtask offloading with logical dependency for IoT applications is focused on. Specifically, subtask dependent graphs are employed to explore the dependency of subtasks and consider the priority of task scheduling. Further, an offloading scheme is put forward for minimizing both task latency and energy consumption of the device with dependency guarantees for all IoT tasks in multi‐server edge networks. Finaly, the simulation results demonstrate that the overall reduction rate is around 14% and relatively stable can effectively reduce task latency in multi‐server edge networks.

In this paper, we investigate the optimal probabilistic constellation shaping design for covert communication systems from a practical view. Different from conventional covert communications with equiprobable constellations modulation, we propose non-equiprobable constellations modulation schemes to further enhance the covert rate. Specifically, we derive covert rate expressions for practical discrete constellation inputs for the first time. Then, we study the covert rate maximization problem by jointly optimizing the constellation distribution and power allocation. In particular, an approximate gradient descent method is proposed for obtaining the optimal probabilistic constellation shaping. To strike a balance between the computational complexity and the transmission performance, we further develop a framework that maximizes a lower bound on the achievable rate where the optimal probabilistic constellation shaping problem can be solved efficiently using the Frank-Wolfe method. Extensive numerical results show that the optimized probabilistic constellation shaping strategies provide significant gains in the achievable covert rate over the state-of-the-art schemes.

This paper investigates the secure transmission in a simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) assisted uplink non-orthogonal multiple access system, where the legitimate users send confidential signals to the base station by exploiting STAR-RIS to reconfigure the electromagnetic propagation environment proactively. Depending on the availability of the eavesdropping channel state information (CSI), both the full CSI and statistical CSI of the eavesdropper are considered. For the full eavesdropping CSI scenario, we adopt the adaptive-rate wiretap code scheme with the aim of maximizing minimum secrecy capacity subject to the successive interference cancellation decoding order constraints. To proceed, we propose an alternating hybrid beamforming (AHB) algorithm to jointly optimize the receive beamforming, transmit power, and reflection/transmission coefficients. While for the statistical eavesdropping CSI scenario, the constant-rate wiretap code scheme is employed to minimize the maximum secrecy outage probability (SOP) subject to the quality-of-service requirements of legitimate users. Then, we derive the exact SOP expression under the constant-rate coding strategy and develop an extended AHB algorithm for the joint secrecy beamforming design. Simulation results demonstrate the effectiveness of the proposed scheme. Moreover, some useful guidance about the quantification of phase shift/amplitude and the deployment of STAR-RIS is provided.

This paper develops a multi-helper non-orthogonal multiple access (NOMA)-enabled mobile edge computing (MEC) system, in order to support massive connectivity. To achieve a tradeoff between the energy consumption and delay, we introduce a novel performance metric, called energy-delay tradeoff, which is defined as the weighted sum of energy consumption and delay. The joint optimization of helper clustering, power allocation and task assignment is formulated as a mixed integer nonlinear programming problem with the aim of minimizing the energy-delay tradeoff. The formulated problem with coupled and 0-1 variables belongs to the NP-hard problem, which cannot be directly solved within polynomial time. To efficiently solve such a challenging problem, we first decouple it into a power allocation and task assignment (PATA) subproblem. Then, with the solution obtained from the PATA subproblem, we equivalently reformulate the original problem as a discrete helper clustering (DHC) problem. For the PATA subproblem, a successive convex approximation (SCA)-based algorithm is proposed. Then, based on the solution obtained from the PATA subproblem, we design a low-complexity matching-based clustering (MBC) algorithm to solve the DHC problem. Simulation results are provided to demonstrate the effectiveness of our proposed algorithm in the compromise of energy consumption and delay.

Abstract This study investigates the physical‐layer security of a terrestrial communication system in the presence of potential unmanned aerial vehicle (UAV) eavesdroppers (UEDs). Due to the line‐of‐sight channels of ground‐to‐air links and the broadcast characteristics of wireless channels, the UEDs have a better chance to eavesdrop terrestrial communication systems compared with the conventional ground eavesdroppers. It indicates that the emerging of UEDs brings new challenges to secure transmissions in terrestrial communication systems. In this study, a UAV is recruited to wisely jam the UEDs by adopting a dynamic three‐dimensional (3D) trajectory, in order to protect the legitimate transmission. To maximally improve the average secrecy rate, the joint optimization of the 3D trajectory of the UAV jammer and legitimate user scheduling as a non‐convex mixed‐integer optimization problem is formulated. To efficiently solve such a challenging problem, a novel enhanced genetic algorithm (EGA), where a combined encoding method and a fitness‐based crossover method are developed to improve the convergence performance, is proposed. Simulation results demonstrate the superior performance of the proposed EGA in terms of the average secrecy rate.

Abstract This paper investigates the reliable computation offloading in non‐orthogonal multiple access enabled mobile edge computing networks, where the short‐packet technique is adopted to meet the stringent latency requirements of delay‐sensitive computing services. To characterize the reliability of computation offloading with finite blocklength coding, a novel analytical framework is developed to approximate the average overall block error probability (AOBEP) by using a double‐case linearization. With the derived approximate expression for AOBEP, the joint optimization of computation workload and transmit power is further investigated, in order to minimize the AOBEP under the computation/communication delay constraints. To tackle the non‐convexity of the formulated problem, the formulated problem is first decomposed into the computation workload problem and the transmit power allocation problem. For the computing workload problem, a closed‐form solution is derived. Then, by applying the derived workload allocation, the power allocation is transformed into the convex form through some approximations and solved by the successive convex approximation technique. Finally, simulation results are provided to demonstrate the reliability enhancement of computation offloading and reveal the relationship between the workload/power allocation and the communication/computation delay.

Covert communication provides high-level security for protecting users' privacy information. In this paper, we analyze the joint impact of an external jammer and channel uncertainty on covert communication in multi-user cognitive radio networks. Meanwhile, to fairly schedule the covert communication over multi-user cognitive radio networks, we propose a fairness secondary user (SU) scheduling scheme, which enables each SU to have the same probability for sending information covertly with the aid of an external jammer. Then, the closed-form expression for the covert rate of the scheduled SU can be obtained. Our results show that the minimal detection error probability and covert rate of the scheduled SU can be significantly improved by exploiting the channel uncertainty and random variation of interference power. Moreover, the impact of interference power on the probability of detection error and the covert rate is noticeable when channel uncertainty is large.

We study the energy efficiency problem for a fog computing system with multiple users and fog nodes. In order to handle various kinds of tasks at the same time, a mixed-task paradigm is proposed to combine both binary offloading and partial offloading. Then, a mixed-task resource allocation problem with the consideration of computation and communication resources is formulated as a mixed integer nonlinear programming problem (MINLP), which cannot be handled by the traditional relaxation algorithm due to the joint design of binary and partial offloading. To solve this problem efficiently, we first adopt a replacement-based method to transform the problem, and then design an augmented Lagrange method (ALM)-based resource allocation scheme. To further accelerate the solution procedure, a novel optimization technique, AMSGrad, is applied to the designed scheme. The performance of the proposed scheme is demonstrated by simulation results.

In this paper, we tackle the joint computation and communication resource allocation problem for mixed-task user-concerned fog computing. To deal with diverse kinds of computing tasks, we propose a mixed-task paradigm to support the co-existence of binary offloading and partial offloading. Considering the impact of users' satisfaction on fog computing service, we employ the user-weighted energy efficiency (UWEE) as the objective of resource allocation and develop a user-concerned mechanism (UCM) to sketch users' social features. Then, under the constraints of users' satisfaction, the resource allocation problem for UWEE maximization is formulated as a mixed integer nonlinear programming problem (MINLP), which cannot be properly solved by the traditional relaxation algorithms due to the co-existence of binary offloading and partial offloading. After transforming the problem with the replacement-based method, an augmented Lagrange method (ALM)-based resource allocation scheme is proposed to iteratively solve this joint optimization problem, in which AMSGrad is employed to accelerate the convergence. Simulation results demonstrate the superior performance of the ALM-based resource allocation scheme in terms of UWEE.

We investigate a secrecy-enhancing design for cooperative downlink and uplink non-orthogonal multiple access (NOMA) transmissions with an untrusted relay. A source uses the NOMA principle to have downlink and uplink transmissions with a near user and a far user, and the communications between the source and the far user are aided by an untrusted relay. To minimize information leakage at the untrusted relay and achieve secure NOMA communications, adaptive downlink and uplink cooperative jamming schemes are proposed, where the far user in downlink and the near user in uplink adaptively emit a jamming signal to the untrusted relay to impair its eavesdropping capability. Both downlink and uplink jamming power are optimized to fully exploit the benefits of the proposed schemes for security enhancement. Then, for each scheme, we quantify the secrecy performance by deriving the ergodic secrecy sum rate lower bound and its scaling law. Finally, computer simulation is used to demonstrate the effectiveness of the proposed adaptive downlink and uplink cooperative jamming schemes and verify the accuracy of the derived analytical results.

This paper investigates the hybrid precoding design in millimeter-wave (mmWave) systems with a fully-adaptive-connected precoding structure, where a switch-controlled connection is deployed between every antenna and every radio frequency (RF) chain. To maximally enhance the energy efficiency (EE) of hybrid precoding under this structure, the joint optimization of switch-controlled connections and the hybrid precoders is formulated as a large-scale mixed-integer non-convex problem with high-dimensional power constraints. To efficiently solve such a challenging problem, we first decouple it into a continuous hybrid precoding (CHP) subproblem. Then, with the hybrid precoders obtained from the CHP subproblem, the original problem can be equivalently reformulated as a discrete connection-state (DCS) problem with only 0-1 integer variables. For the CHP subproblem, we propose an alternating hybrid precoding (AHP) algorithm. Then, with the hybrid precoders provided by the AHP algorithm, we develop a matching assisted fully-adaptive hybrid precoding (MA-FAHP) algorithm to solve the DCS problem. It is theoretically shown that the proposed MA-FAHP algorithm always converges to a stable solution with the polynomial complexity. Finally, simulation results demonstrate the superior performance of the proposed MA-FAHP algorithm in terms of EE and beampattern.

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 NU-FU pair with using NOMA; Cooperative NOMA mode, in which the scheduled NU receives the messages intended by both scheduled users from the BS, and then forwards the message intended by the scheduled FU. For the OA-NOMA strategy, a scheduling candidate acquisition method and a probabilistic user pair scheduling scheme are proposed to guarantee the transmission reliability and improve the scheduling fairness, respectively. To evaluate the scheduling fairness, we develop a max-min fairness criterion and show that the OA-NOMA strategy approximately achieves max-min fairness. The reliability of the OA-NOMA strategy is also evaluated in terms of outage probability and diversity order. For the outage probability, we derive an approximate expression and numerically verify its tightness. For the diversity order, we show that the proposed OA-NOMA strategy achieves a diversity order of M.

We study secure communications with an untrusted relay for a cooperative non-orthogonal multiple access (NOMA) system, where a base station (BS) serves a near user (NU) and a far user (FU) by the NOMA principle, and transmission between BS and FU is aided by an untrusted relay. We propose an adaptive jamming scheme to enhance transmission security, in which FU is asked to adaptively emit a jamming signal to confuse the untrusted relay. The transmission rate for jamming is designed to ensure that only NU can decode the jamming signal correctly, and the jamming power is optimized for maximizing the secrecy sum rate. We analyze the security performance of the proposed scheme and derive the ergodic secrecy sum rate and its scaling law. Simulation results are presented to validate the effectiveness of the proposed adaptive jamming scheme.

This paper investigates the hybrid precoding design in millimeter-wave (mmWave) systems. To jointly consider the spectral efficiency and energy consumption, we propose an adaptive hybrid precoding structure, where a switch-controlled connection is deployed between every antenna and every radio frequency (RF) chain. To maximally enhance the spectral-and-energy efficiency under this structure, the joint optimization of the on-off states for switch-controlled connections and the hybrid precoding matrices is formulated as a non-convex problem. To efficiently solve this problem, we first propose an alternative limited Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) based algorithm to determine the hybrid precoders. Then, using the alternative L-BFGS algorithm, a greedy algorithm is proposed to jointly optimize the hybrid precoders and the on-off states of switch-controlled connections. It is theoretically shown that, this alternative L-BFGS based algorithm always converges to a stationary point. Further, the convergence of proposed greedy algorithm is also theoretically proved and validated by simulations. Simulation results also demonstrate that the proposed hybrid precoding achieves a superior tradeoff between the spectral efficiency and energy consumption.

This paper investigates the resource allocation in millimeter wave ultra dense networks, in which the beam assignment and sub-band allocation are jointly considered. Motivating to maximize the sum rate of the network conceived, the optimization problem is formulated as a mixed integer non-linear programing (MINLP) problem, which involves allocating the novel three-dimensional resource blocks (RBs) defined in beam (B), time (T), and frequency (F) dimension, respectively. To tackle the formulated MINLP problem, we propose the low-complexity resource allocation scheme, including the so-called best option first (BOF) beam assignment algorithm, and the many-to-one matching with externalities (M2O-ME) sub-band allocation algorithm. In particular, the BOF beam assignment algorithm is first carried out to coordinate the RBs in terms of T- and B-dimension. Then, with the aid of the mechanism of many-to-one with externalities, the M2O-ME sub-band algorithm is implemented to find the optimal sub-band allocation (i.e. RB allocation in F-dimension) solution. Finally, our simulation results show that the proposed resource allocation scheme can significantly outperform the existing schemes in terms of sum rate of the networks. Therefore, we can conclude that the proposed resource allocation scheme can be considered as a promising candidate for practical ultra dense small-cell networks with mmWave capability.

This paper proposes a novel design of cooperative non-orthogonal layered multicast multiple access in a heterogeneous network, where the information is encoded into the messages of high priority (HP) and low priority (LP). Two types of multicast users coexist in the network: 1) regular users (RUs), which are located far away from the base station (BS) and expect to decode only the HP message (due to the weak channels), and 2) advanced users (AUs), which are located close to the BS and expect to decode both HP and LP messages. To improve the reliability of layered multicast, we consider that the successful AUs (those AUs who successfully decode the HP and LP messages) serve as potential relays to assist other AUs/RUs. Based on this idea, two novel cooperation strategies are proposed for different cases of channel information availability. For each proposed strategy, we derive closed-form exact outage probabilities of AUs and RUs and then further analyze their diversity orders. Moreover, considering that the layered multicast is outage-constrained, we theoretically evaluate the energy consumption of both strategies and demonstrate their energy saving gains over the direct non-orthogonal multiple access for layered multicast. Finally, our theoretical analysis is verified by numerical results, and the advantages of the proposed strategies are also demonstrated.

In this paper, we investigate secure communication for an untrusted relay network, in which a source equipped with NS antennas communicates to M users with the help of an untrusted relay. To protect the data confidentially while concurrently relying on the untrusted relays, joint antenna and user selection scheme has been proposed with the aid of cooperative jamming. Furthermore, the impacts of both the number of antennas and the number of users on system performance are studied. Both the secrecy outage probability (SOP) and ergodic secrecy rate (ESR) are derived in closed form, and the secrecy diversity order of the considered networks is proved to be min(NS, M/2). Compared with the traditional single antenna and single source-destination scenario, both SOP and ESR can achieve a great improvement owing to the mutual effects of antenna diversity and user diversity. In addition, numerical results are conducted to demonstrate the validity of the proposed scheme.

This paper proposes a novel design of cooperative non-orthogonal multiple access (NOMA) for layered multicast, where the information is encoded into the messages of high-priority (HP) and low-priority (LP). Two types of multicast users coexist in the system: 1) regular users (RUs), which locate far away from the base-station (BS) and demand only the HP message; 2) advanced users (AUs), which locate close to the BS and demand both HP and LP messages. To improve the reliability of layered multicast, an opportunistic cooperative NOMA multicast strategy is proposed, in which one successful AU is selected to forward both HP and LP messages. For the proposed strategy, we derive closed-form exact outage probabilities of AUs and RUs. By further carrying out the asymptotic analysis, the achieved diversity orders are shown to be not less than the number of AUs, i.e., full diversity is achieved. Finally, numerical results verify the theoretical analysis and demonstrate the superiority of the proposed strategy.

As a flexible network sharing mechanism, wireless network virtualization (WNV) can significantly improve the resource utilization and reduce the overall expense for the next generation wireless networks. Considering the users' common interests on popular contents, we introduce wireless multicast into wireless virtual networks. To serve the users who have requests on the same content via multicast transmission, both the virtual resources and content can be shared simultaneously. Thus, the virtual resources and backhaul bandwidth can be further released. In this paper, we propose a novel WNV based multicast system. Subsequently, the multicast group forming and sub-channel allocation strategies are jointly investigated in considered frameworks. Then we formulate the strategies as an integer nonlinear programming problem. Furthermore, we propose a heuristic algorithm with the aid of cutting-plane method to tackle the problem. Finally, Simulation results verify that our proposed scheme can significantly enhance the total utility of wireless virtual networks with lower backhaul usage and the proposed heuristic algorithm can achieve a perfect performance.

This paper proposes a new optimal time-switching relaying protocol for wireless-powered decode-and- forward relay networks. The relay has no embedded power supply, and it has to harvest energy from radio-frequency signals transmitted by the source. In specific, we focus on the time-switching mechanism where a fraction of block time is used for energy harvesting (EH) and the remaining is used for information transmission (IT). Equipped with a rechargeable battery, the relay can accumulate the harvested energy and choose a proper transmit power. For system throughput maximization, we propose an optimal time-switching relaying (TSR) protocol to optimally determine the EH time and the relay power, according to the channel state and the battery state. Interestingly, we prove that the optimal EH time is a discrete two-state variable, i.e., the whole block time is used for either IT or EH. With the proposed TSR relaying protocol, the analytical expression for the system throughput is derived. Simulations validate the analysis and demonstrate that a significant throughput improvement can be achieved.

Recently, there are increasing requirements of security in wireless communications, especially for the multiuser systems. In this study, the authors consider the security of two‐hop cooperative multicast networks with an untrusted relay. An energy harvesting destination aided cooperative jamming framework is proposed to protect information from being intercepted by the untrusted relay. For the multiple destinations, a maximum interference jammer selection (MIJS) scheme is proposed to further improve physical layer security. Then the ergodic secrecy rate (ESR) for MIJS scheme is investigated and both the lower bound of ESR and the approximation of ESR are obtained. Finally, the effect of both the energy arrival rate and the number of destination nodes on ESR has been shown via numerical simulations. It can be revealed that as the number of destinations increases, the ESR is determined with two common behaviours regarding the multicast nature and energy arrival rate: (i) multicast nature forces the secrecy rate to decrease with the increasing number of destinations and (ii) the probability that a jammer exists increases with the increasing number of destinations but limited to one.

The inherent broadcast characteristics of wireless medium make wireless data transmission difficult to be shielded from unintended recipients. As such, secure communication over wireless channels becomes a critical issue in the design of wireless networks. In this study, the authors study cooperative jamming and power optimisation in untrusted relay networks to improve physical layer security. By exploiting the direct link, a source‐based jamming (SBJ) scheme is proposed to hinder the untrusted relay from intercepting the confidential message. Considering the total power budget, a power allocation strategy is also proposed to optimally determine the power of source and untrusted relay as well as the power of information and jamming signals. Furthermore, to evaluate the secrecy performance of the proposed SBJ scheme with the power allocation strategy, tight lower bound of ergodic secrecy capacity and asymptotic secrecy outage probability are derived in closed form. Simulation verifies the advantages of the proposed SBJ scheme and the power allocation strategy.

Optimal relay selection is investigated for secure cooperative communications against an adaptive eavesdropper that can perform eavesdropping if the eavesdropping link has good channel quality or perform jamming otherwise. A number of decode-and-forward relays are available for legitimate communications, among which one relay can be selected to help. For legitimate communications, three cases for availability of the eavesdropping channel information are considered: full channel knowledge, partial channel knowledge, and statistical channel knowledge. An optimal relay selection scheme is proposed for each case. For the first and third cases, exact secrecy outage probability expressions in closed form are derived, and for the second case, an approximate secrecy outage probability is derived, which is tight in the high main-to-eavesdropper ratio regime. Moreover, secrecy diversity order for the proposed relay selection scheme in each case is also derived, which is shown to be a full secrecy diversity. Finally, numerical results are given to verify the theoretical analysis derived in this paper.

This paper designs a novel non-orthogonal multiple access (NOMA) unicast-multicast system, where a number of unicast users (those who require different messages) and a group of multicast users (those who require identical message) share the same time/space/frequency resource. For the designed NOMA unicast-multicast system, an efficient two-phase cooperation strategy is proposed to improve the reliability of all users. In the first phase, the base station (BS) broadcasts a superposed message consisting of all users' information. In the second phase, a multicast user is selected to forward the information intended by unsuccessfully decoded unicast and/or multicast users. Moreover, the multicast user selection is investigated under two different power allocation (PA) approaches: 1) fixed PA (FPA), in which the PA coefficients for both the phases are predetermined, and 2) dynamic PA (DPA), in which the PA coefficients for the first phase are predetermined, while the PA coefficients for the second phase are dynamically determined based on instantaneous channel information. Under the FPA approach, a best user selection (BUS) scheme (called F-BUS) is proposed to minimize the outage probability. Under the DPA approach, the local optimal PA coefficients for the second phase are derived in closed form first. Based on the derived PA coefficients, a BUS scheme (called D-BUS) is then proposed for outage probability minimization. To verify the reliability of the proposed cooperation strategy with employing the BUS schemes, we theoretically analyze the outage probability as well as diversity orders. It is shown that the proposed cooperation strategy achieves diversity orders equal to the number of multicast users, indicating that the inherent diversity orders offered by the multicast users are fully exploited. Finally, simulation results are presented to validate the theoretical results and demonstrate the advantages of the proposed cooperation strategy and the BUS schemes.

Successive relaying has recently emerged as a spectral-efficient technique for cooperative wireless communications. However, in scenarios with uncertain accuracy of instantaneous channel state information (CSI), the scope of conventional two-path successive relaying protocol shrinks. This is due to the challenges of cancelling inter-relay interference (IRI) and detecting signals efficiently without specific CSI. The two challenges motivate us to propose a novel double listening 3-path successive relaying (DL3PSR) protocol to mitigate the successive relaying's dependence on accurate instantaneous CSI. We overcome the first challenge by proposing a blind IRI cancellation technique, and its effectiveness is proven. After blind IRI cancellation, the challenge of efficient signal detection is overcome by robust cooperative non-coherent detection, which consists of exclusive OR (XOR) demodulation and joint decoding. Based on constellation mapping, XOR demodulation is designed to demodulate M-ary phase-shift keying symbols without instantaneous CSI. Moreover, joint forward and backward decoding strategy is proposed to improve the robustness of data detection by retrieving two independent versions of the original data. Furthermore, the detection threshold, bit error probability, and achievable rate of DL3PSR are theoretically obtained. Simulations verify that in scenarios without full knowledge of CSI, DL3PSR protocol outperforms conventional two-path successive relaying in bit error performance and that the rate of DL3PSR is close to that of the full-duplex relaying. Copyright © 2016 John Wiley & Sons, Ltd.

The high‐speed mobility of modern transportation worsens the situation of unstable direct links and imprecise channel estimation, which poses challenges on fast and reliable data delivery in vehicular ad hoc networks (VANETs). The goal of the proposed scheme is to provide high‐speed full‐duplex relaying connectivity for unstable direct links, and reliable information detection without precise channel state information (CSI) in VANETs. In the proposed scheme, full‐duplex relaying connectivity is provided by differential successive relays (DSRs) at roadside or inside other vehicles. To improve robustness of DSR without specific CSI, efficient blind interference cancellation is presented to mitigate inter‐relay interference. Meanwhile, reliable information detection without precise CSI is enabled by superposition coding with differential modulation. Furthermore, the advantages, applications of DSR and complexities for real‐world implementation are discussed, and the decision rule, bit error probability and ergodic capacity are theoretically obtained. Numerical results verify significant improvements in the performance of the proposed scheme when compared with conventional schemes with half‐duplex relays and frequent channel estimation in VANETs.