Driven by the growing popularity of mobile applications, mobile cloud computing has been envisioned as a promising approach to enhance computation capability of mobile devices and reduce the energy consumptions. In this paper, we investigate the problem of multi-user computation offloading for mobile cloud computing under dynamic environment, wherein mobile users become active or inactive dynamically, and the wireless channels for mobile users to offload computation vary randomly. As mobile users are self-interested and selfish in offloading computation tasks to the mobile cloud, we formulate the mobile users' offloading decision process under dynamic environment as a stochastic game. We prove that the formulated stochastic game is equivalent to a weighted potential game which has at least one Nash Equilibrium (NE). We quantify the efficiency of the NE, and further propose a multi-agent stochastic learning algorithm to reach the NE with a guaranteed convergence rate (which is also analytically derived). Finally, we conduct simulations to validate the effectiveness of the proposed algorithm and evaluate its performance under dynamic environment.

This paper investigates physical layer security (PLS) in cognitive radio inspired non-orthogonal multiple access (CR-NOMA) networks with multiple primary and secondary users. For managing the interferences among the users and guaranteeing the quality of services (QoS) of primary users, a new secure NOMA transmission strategy is designed, where the primary and secondary users are paired by their channel gains, respectively, and employing power-domain NOMA to transmit signal. Then, the closed-form expressions for connection outage probability (COP), secrecy outage probability (SOP) and effective secrecy throughput (EST) are derived of the primary users over Nakagami-m fading channels when the secondary users are considered as eavesdroppers. Typically, the secrecy performance can be improved by pairing the primary users with best channel gains or reducing the number of secondary users. In addition, we have also investigated the performances of secondary users by deriving the closed-form expressions of COP and throughput of secondary network. Significantly, the power allocation factors of primary users and secondary users provide a tradeoff between the performance of primary and secondary users. Furthermore, simulations are conducted to verify our analysis results and provide insights into the impact of the parameters on system performance.

In this letter, we investigate the channel estimation problem for MIMO wireless communication systems with movable antennas (MAs) at both the transmitter (Tx) and receiver (Rx). To achieve high channel estimation accuracy with low pilot training overhead, we propose a tensor decomposition-based method for estimating the parameters of multi-path channel components, including their azimuth and elevation angles, as well as complex gain coefficients, thereby reconstructing the wireless channel between any pair of Tx and Rx MA positions in the Tx and Rx regions. First, we introduce a two-stage Tx-Rx successive antenna movement pattern for pilot training, such that the received pilot signals in both stages can be expressed as a third-order tensor. Then, we obtain the factor matrices of the tensor via the canonical polyadic decomposition, and thereby estimate the angle/gain parameters for enabling the channel reconstruction between arbitrary Tx/Rx MA positions. In addition, we analyze the uniqueness condition of the tensor decomposition, which ensures the complete channel reconstruction between the whole Tx and Rx regions based on the channel measurements at only a finite number of Tx/Rx MA positions. Finally, simulation results are presented to evaluate the proposed tensor decomposition-based method as compared to existing methods, in terms of channel estimation accuracy and pilot overhead.

Future wireless networks have requirements of large connections, low power consumption, high reliability, and strong security. Considering the abundant available bandwidth of millimeter wave (mmWave) and the large line-of-sight (LOS) link probability of air-ground channel, in this paper, we develop a framework to study security, reliability and energy coverage performance of the downlink mmWave SWIPT UAV networks under non-orthogonal multiple access (NOMA) and orthogonal multiple access (OMA) schemes, where a UAV serves two types of authorized IoT devices in the presence of multiple passive eavesdroppers. Directional modulation (DM) is also used to improve the physical layer security performance. First, the analytical expressions for connection outage probability (COP), secrecy outage probability (SOP) and effective secrecy throughput (EST) of the users with high rate security requirement (HRSR) under NOMA and OMA schemes are derived using stochastic geometry. Then, we optimize the active antenna selection of DM using adaptive genetic simulated annealing algorithm to further improve the secrecy performance based on the obtained analytical results. Finally, the closed-form expressions for the COP and energy-information coverage probability (EICP) of the energy-constrained users with low-rate requirement (ECLR) under NOMA and OMA schemes are obtained. Numerical and simulation results provide interesting insights into the influence of various parameters on the tradeoff between the reliability and security for the HRSR user, and the tradeoff between the reliability and energy coverage for the ECLR user. Moreover, the EST of NOMA scheme outperforms OMA at low transmit power and high codeword transmission rate.

In this letter, we investigate the robust and secure beamforming (RSBF) in an intelligent reflecting surface (IRS) aided millimeter wave (mmWave) multiple input single output (MISO) system, where multiple single antenna eavesdroppers (Eves) are arbitrarily distributed nearby the legitimate receiver (Bob). Considering the channel state information (CSI) of cascaded wiretap channels is imperfectly known at the legitimate transmitter (Alice), the RSBF design problems to maximize the worst case of achievable secrecy rate (ASR) are formulated under the total transmission power and unit-modulus constraints. Since the problems are difficult to solve optimally due to their non-convexity and coupled variables, we substitute the wiretap channels by a weighted combination of discrete samples and propose a RSBF scheme based on alternating optimization and semidefinite relaxation (SDR) techniques, for both colluding and noncolluding eavesdropping scenarios. Simulation results show that the proposed RSBF scheme can effectively improve the ASR and also outperforms other benchmark schemes.

It is crucial to consider timely status updates for machine type communication (MTC) in some scenarios, where a controller continuously obtains state information of targets from a sender to complete control or monitoring tasks, such as vehicular networking and environmental detection. In this work, we measure the timeliness of the status by the recently proposed age of information (AoI) metric. Different from the previous works about AoI, we consider the short packet feature of MTC in our system, where status packets will suffer from a significant packet error rate. Considering that the status packets may not be decoded by the receiver correctly, this work investigates the performance of MTC under traditional protocol (the sender discards the error status packets directly) and automatic repeat-request (ARQ) protocol (the sender retransmits the error status packets), and gets the approximated closed expressions of the average AoI, respectively. Based on the closed-form expressions of the average AoI, we design two suboptimal blocklength to minimize the average AoI under the two protocols. Numerical results verify the correctness of theoretical analysis, and show that the proposed scheme can achieve almost the same optimization performance as the exhaustive search method. What's more, in the case of different packet generation rates, we find that the ARQ/traditional protocol can achieve better performance in low/high packet generation rate scenarios, respectively.