In this paper, we investigate secure transmission for intelligent reflecting surface (IRS)-aided wireless communication systems, where the IRS assists Alice in delivering confidential information to the legitimate user while preventing leakage to eavesdroppers. To improve physical layer security (PLS), we jointly optimize transmit beamforming (TB) at Alice and passive beamforming (PB) at the IRS. Due to imperfect channel state information (CSI) related to eavesdroppers, the joint TB and PB problem is formulated as a maximization of the expected minimum secrecy rate problem with constant-modulus constraints for IRS. To solve this problem, we first address the expectation operation in the objective function by employing Jensen’s inequality. Then, the deterministic max-min sum-of-logarithms problem is reformulated as an equivalent minimization weighted minimum mean-square error (WMMSE)problem with a bi-quadratic objective function in terms of TB and PB. This problem is solved by the proposed alternating optimization algorithm, where TB and PB are alternately optimized. Specifically, TB is optimized by solving a convex quadratic constrained quadratic programming (QCQP) subproblem, while PB is optimized by applying the penalty convex-concave procedure (PCCP). Simulation results demonstrate that the proposed algorithm achieves good secrecy performance.

In this paper, we present a unmanned aerial vehicles (UAV) relay covert communication scheme assisted by an intelligent reflecting surface (IRS), which is exploited to improve channel quality between transmitter and legitimate user. Specifically, we formulate a nonconvex optimization problem to maximize average covert rate, where trajectory of the UAV, transmit beamforming (TB) at Alice, and passive beamforming (PB) of the IRS under the covert constraint are considered. To tackle the difficult problem, we divide it into trajectory optimization (TO) subproblem, TB optimization subproblem, and PB optimization subproblem and then solve them alternately via successive convex approximation algorithm and semidefinite relaxation technique respectively. Numerical results demonstrate the effectiveness of the proposed approach and provide insights on how covert rate is influenced by the trajectory, TB, and PB.

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.

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.

Millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) offers a promising technique to fulfil the high data demand and connectivity of the Internet-of-Things (IoT) and 5G communications because it owns valuable and unknown spectrum resources. Using massive antennas with recently introduced drone-enabled aerial computing platforms, named unmanned aerial vehicles (UAVs), can cast high energy consumption if fully-digital precoding is employed at the UAVs. Using hybrid precoding at a UAV can reduce hardware complexity and energy consumption but is challenging with a need for joint optimization of three precoding matrices at the UAV (sixth-order polynomial objective function). In this paper, we propose to decompose the original UAV hybrid precoding challenge into three subproblems and develop a coordinated descent optimization (CDO) algorithm to solve the three problems recursively. In addition, the convergence and complexity of this new technique are analyzed. Numerical studies indicate the improved effectiveness of the proposed solution over existing solutions.

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.

This paper investigates the sensor selection problem for time difference of arrival (TDOA) localization in wireless sensor networks. Specifically, a multi-objective optimization problem is formulated in which a Boolean vector is involved to find the best tradeoff between the localization accuracy and the energy consumption. The ε- constraints method is introduced to convert the original multi- objective optimization problem to a tractable single-objective problem. To solve the converted sensor selection problem, we propose the polyblock outer approximation (POA) algorithm based on discrete monotonic optimization (DMO) in order to find the global optimal solution, which however can not be obtained by the traditional semidefinite relaxation (SDR) approach. Further, for the sake of practical implementation, we propose another two suboptimal algorithms, namely, POA-based accelerated cutting (POA-AC) algorithm and POA-based monotonic cutting (POA-MC) algorithm. Simulation results validate that the localization accuracy for sensors selected by the POA-AC algorithm and POA-MC algorithm is greater than the semidefinite relaxation (SDR) solution and achieves the same results as that by the exhaustive search method.

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 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.

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.

Beamforming with multiple data streams, or named as precoding, plays a significant role in millimeter-wave massive MIMO systems. If properly designed, the precoding can improve spectral efficiency of the system and compensate for the degradation caused by channels. Although the classical full-digital precoding can achieve the optimal performance, it is too expensive for implementation. To reduce cost and power consumption, some hybrid structures of precoding are recently proposed while their precoding schemes have not been extensively studied. In this paper, the mathematical model of the precoding for relay assisted system is reconstructed. The objective function is highly non-convex and has some complex constraints. Especially the block-diagonal constraint and constant-modulus constraint make the classical precoding methods based on singular value decomposition not applicable. We design an algorithm based on alternating direction method of multipliers to optimize the objective function. By deliberating over the iteration order of the variables, we give the convergent condition of the proposed algorithm. This paper focused on sub-connected precoding structures since they have more constraints. Meanwhile, the proposed algorithm can be applied to full-connected structures simply. We present the simulation results which indicate that the proposed algorithm can provide a near optimal solution to the original precoding problem.

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.