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In this paper, we investigate a hybrid satellite-unmanned aerial vehicle (UAV) relay network (HSURN) with rate splitting multiple access (RSMA), where the terminal transmits a superposition of the common and private signals with different power levels, and the UAV operates in half-duplex decode-and-forward (DF) mode to assist communication between terminals and satellites. With the RSMA scheme, we investigate the joint optimization problem of terminal-UAV association (TUA) and power allocation (PA) of both the terminals and UAVs for the common and private signals under the constraint of limited resources to maximize the achievable sum rate. Given the non-convexity of the original problem, it is decoupled into two subproblems. The TUA subproblem is solved via deep Q-network (DQN). The PA subproblem is solved by successive convex approximation (SCA) and Lagrange dual approach. Afterward, an alternate iterative algorithm is developed by iteratively performing the outputs of two subproblems. Numerical results verify that compared with the traditional transmission schemes, our proposed RSMA scheme is more beneficial to information transmission. Compared with the existing algorithms, the proposed algorithm can achieve the flexible association between UAV and the serviced terminal by adjusting the splitting strategy of common and private signals in dynamic network environment.

The quality of service (QoS) and lifetime of wireless sensor networks (WSNs) are severely degraded by coverage holes generated by random deployment or battery exhaustion of sensors. This work firstly introduces a novel confident information coverage CIC) model to dramatically reduce the density of sensor nodes and accurately detect confident information coverage holes (CICHs). Then, the problem of repairing confident information coverage holes (RCICHs) for big data collection in a large-scale heterogeneous WSN (LS-HWSN) which widely spreads over a geographic area with thousands of stationary sensor nodes and mobile sensor nodes is formulated, called as RCICH problem, which is to effectively repair CICHs considering that the transmitted data velocity of sensor nodes is different. Furthermore, we prove it to be NP-completeness. The target of the problem is to find a subset of mobile sensor nodes from all mobile sensor nodes while minimizing the amount of lost throughputs LTs) of all dispatched mobile sensor nodes or maximizing the amount of repairing transmission times (RTTs) for all dispatched mobile sensor nodes, with different objectives. Finally, based on the CIC model and the data-centric perspective, two heuristic schemes including a centralized dispatch scheme and a distributed dispatch scheme are proposed to effectively solve the RCICH problem. Simulation results show that the proposed schemes effectively repair CICHs while increasing the QoS and lifetime of the LS-HWSN with the topology control of a fan-shaped clustering (FSC) protocol.

In order to improve the security performance of multiuser visible light communication (VLC) and facilitate the secure application of optical wireless communication technology in Internet-of-Things, we investigate the physical-layer security in a multiuser VLC system with non-orthogonal multiple access (NOMA). When the light-emitting diode (LED) transmitter communicates with multiple legitimate users by downlink NOMA, both single eavesdropper and multi-eavesdropper scenarios are considered. In the presence of single eavesdropper, based on transmission characteristics of the optical wireless channel, with known instantaneous channel state information (CSI) of the NOMA legitimate channels and statistical CSI of the eavesdropper channel, an exact expression of secrecy outage probability (SOP) is derived, which acts as a benchmark of the security performance to guide selecting or optimizing parameters of the LED transmitter and the photodiode receiver of NOMA legitimate users. In the multi-eavesdropper case, based on the spatial distribution of legitimate users and eavesdroppers, the SOP is obtained via a stochastic geometry theory, so as to guide the NOMA legitimate users to keep away from the area with high eavesdropper density. For typical parameters of the indoor LED transmitter and the PD receiver, simulation results show that the SOP performance improves with the increasing of LED transmission power or transmission signal-to-noise ratio (SNR) in both scenarios. Specifically, in the single eavesdropper case, enlarging the channel condition difference of user groups or deviating the eavesdropper from the given user group can improve the SOP performance, and for a given NOMA legitimate user, the SOP eventually settles around 0.2 while the semiangle at half illuminance of the LED varies between 15° to 60°. In the multi-eavesdropper case, we can get a better SOP performance when reducing the eavesdropper density or the semi-angle at half illuminance of the LED for a given eavesdropper density.

To achieve the maximum network energy efficiency (EE) and guarantee the fairness of EE among cognitive users (CUs), respectively, in the massive multiple-input multiple-output cognitive radio network, we investigate two power optimization problems: network EE optimization problem (NEP) and fair EE optimization problem (FEP) under a practical power consumption model. Because of the fractional nature of EE and the interference, both NEP and FEP are non-convex and NP-hard. To tackle these issues, we propose two energy-efficient power control algorithms, in which we decompose NEP/FEP into two steps, and solve them with an alternating iterative optimization scheme. Specifically, in the first step, for an initial transmit power, the maximum network EE/fair EE is achieved by the bisection method based on fractional programming; then, with the achieved EE, in the second step, the adapted optimal transmit power can be obtained by an efficient iterative algorithm based on sequential convex programming. These two steps are performed alternately until the stop conditions are reached. Numerical results confirm the fast convergence of these proposed algorithms and demonstrate their effectiveness with high network EE and well fairness of EE among CUs. Furthermore, it is illustrated that, under a practical power consumption model, more cognitive base station antennas would cause some loss of network EE but bring some improvements on the network spectral efficiency (SE), whereas higher circuit power consumption would reduce the network EE but only slightly affect the network SE.

This paper concerns with a relay-aided massive multiple input multiple output (MIMO) cellular network. The exact closed-form expressions of both spectral efficiency (SE) and energy efficiency (EE) are obtained for downlink single-cell multi-user multi-relay massive MIMO transmission in the pilot-contaminated regime, where the number of users is larger than the pilot sequence length. Based on the theoretical results of SE and EE, we investigate the effects of some system parameters [such as number of antennas at the base station (BS), transmit power at the BS, and transmit power of each relay station (RS)] on system performance, and achieve the tradeoff between SE and EE by power control. Specifically, the tradeoff problem is solved by joint optimization over transmit power P of the BS and transmit power pr of each RS, so as to maximize EE while satisfying the SE requirement. With the proposition that EE function is strictly quasi-concave with either P or pr, we propose two optimization methods: 1-D searching and alternate optimization. Comparatively, the former achieves a better performance, while the latter has a lower complexity. Simulation results validate the effectiveness of the two methods.

In this paper, we consider a non-regenerative relay network supporting simultaneous wireless information and power transfer, in which the energy harvesting relay is powered by radio-frequency signals from the source node. Assuming imperfect channel state information from the source/relay to the destination/eavesdropper, we investigate the artificial noise-aided secure robust beamformer that minimize the transmission power at the relay, while guaranteeing the secrecy rate constraint and the transmit power constraint at the relay. In particular, two types of energy harvesting strategies are considered termed power splitting (PS) and time switching (TS), respectively. These constraints make the optimization problems formulated non-convex and challenging, which are efficiently solved by using the S-procedure and semidefinite relaxation techniques to formulate a tractable approximated version of the original problems. Numerical results show the effectiveness of the proposed robust beamforming schemes. Furthermore, the PS strategy performs better than the TS strategy.

This paper concerns with a wireless-energy-transfer (WET)-enabled massive multiple-input-multiple-output (MIMO) system with superimposed pilot (SP)-aided channel estimation. Unlike the conventional WET-enabled frame transmission schemes, with the aid of SP, both the uplink (UL) channel estimation and wireless information transmission (WIT) that powered by the downlink (DL) WET can be operated simultaneously, and thus provide the potential for improving the UL achievable throughput. The impact that the SP has on the performance of such a WET-enabled massive MIMO system is mathematically characterized, and the optimal solution, including the SP power-allocation and the ratio of time-allocation between the duration of UL WIT and DL WET, is derived with regard to maximize the UL achievable throughput. Numerical results demonstrate the proposed SP-aided WET technique yields a superior performance than the conventional pilot-only-based schemes.

This paper proposes a roadside unit (RSU)-coordinated synchronous multi-channel medium access control (MAC) scheme for vehicular ad hoc networks (VANETs). The proposed scheme allows the on board unit (OBU) to reserve service channels (SCHs) on the control channel (CCH) during almost the whole synchronous interval and supports simultaneous transmissions on different SCHs. It enhances the performance of VANETs and decreases the CCH congestion. Moreover, we use RSU to record the rendezvous information and broadcast it to the OBUs. This method avoids the multi-channel hidden terminal problem. An analytical model is developed to evaluate the aggregate throughput on SCHs. This model considers the following factors: non-safety message transmission probability in each synchronous interval, average size of the non-safety message, and the number of OBUs. Furthermore, the requirement of obtaining the maximum throughput is computed. Simulation results are provided to validate the analytical model and to demonstrate the improvement in throughput. The results indicate that the proposed scheme can provide higher aggregate throughput than that of the vehicular enhanced multi-channel MAC and IEEE 1609.4, and better performance in CCH congestion control especially under high network load conditions.