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This letter studies the secure transmission issue of non-orthogonal multiple access (NOMA) based cognitive radio networks (CRNs) with imperfect channel state information (CSI), where the secondary user (SU) transmitter aims to transmit the normalized messages to two receivers ${U_{a}}$ and ${U_{b}}$ , and concurrently ${U_{b}}$ with full-duplex (FD) ability implements jamming to confuse the eavesdropping of the illegal user while causing zero interference to the primary user and ${U_{a}}$ . Under this setup, the novel exact closed-form expressions of connection outage probability (COP), secrecy outage probability (SOP) and effective secrecy throughput (EST) for each SU receiver under Rayleigh fading channels are derived. Simulation results are presented to demonstrate that: 1) the proposed scheme can achieve pretty good security and reliability performance, but there exist trade-off between such two indicators; 2) the FD-NOMA operation performs better than the half-duplex (HD) NOMA and HD orthogonal multiple access (OMA) in term of EST.

This letter studies the legitimate eavesdropping with one full-duplex monitor (E) in a suspicious relaying system, where one suspicious transmitter (S) communicates with one suspicious destination (D) with the help of one suspicious unmanned aerial vehicle-based relay (U). Under this setup, E aims to maximize its eavesdropping rate by overhearing the suspicious messages from S/U and optimizing the power of jamming U/D concurrently. However, given specific jamming environment, U could be adaptively deployed to maximize the communication rate of the suspicious system, which brings the fundamental challenge for E to figure out the exact jamming effect. Hence, generally successive convex approximation for determining the corresponding deployment of U and exhaust search over the jamming power is required to achieve the optimal solution. To decrease the high complexity of the optimal strategy, one novel heuristic scheme is further proposed, in which one sub-optimal jamming power is derived immediately. Simulations present the considerable gain of the proposed optimal and heuristic schemes compared to some intuitive schemes.

This letter studies the proactive eavesdropping with one half-duplex legitimate monitor (E) over the wireless-powered multichannel suspicious system, where the suspicious transmitter (ST) proceeds energy harvesting from the power beacon and then communicates with the suspicious destination (SD) via $N$ parallel channels. Under this setup, one jamming-assisted eavesdropping scheme is proposed to maximize the ergodic eavesdropping rate at E. Specifically, we first fix the number of jamming channels $K$ at E, and then reveal that E should jam with maximum power over these $K$ channels to force the ST to allocate more power over the other $N - K$ channels, so as to maximally increase the perceived power at E over the corresponding $N - K$ channels. Armed with this, to maximize the ergodic rate, the following work is only to find the optimal $K$ with simple search. Moreover, one closed-form sub-optimal $K$ is derived for practical implementation. Results present the great gain achieved by the proposed scheme compared to conventional passive eavesdropping and the effectiveness of the sub-optimal $K$ .

This letter studies the proactive eavesdropping in a suspicious decode-and-forward relay system, where the suspicious communication is divided into transmitter-to-relay (ST-SR) phase and relay-to-destination (SR-SD) phase with partial channel selection over $N \ge 2$ orthogonal channels, and the monitor (E) can only jam/overhear the E-SR/SR-E link over $M \le N$ sub-channels for practicality. Under this framework, with strict proof we first theoretically present the impact of jamming power and number of jamming channels selected by E on its eavesdropping success probability (ESP), and then reveal a fundamental trade-off: given jamming power (number of jamming channels), jamming with more channels (power) reduces the suspicious rate for E to overhear more clearly, but degrades the preconditions for successful eavesdropping. Results verify our obtained conclusions and show that the proposed jamming-assisted eavesdropping scheme with simple search method achieves pretty good performance compared with some intuitive schemes.

This letter studies the Unmanned Aerial Vehicles (UAVs)-assisted proactive eavesdropping in the suspicious amplify-and-forward multi-relay system, where the suspicious transmitter based on opportunistic relaying protocol selects one best suspicious relay to communicate with the suspicious destination. In addition, we assume each UAV hovers over one specific relay for the purpose of jamming or eavesdropping, which is only valid for this relay due to the limited coverage of the UAVs and the dispersion between these relays. Moreover, the UAVs used for jamming cannot implement eavesdropping concurrently due to the half-duplex constraints. Under this setup, with detailed analysis and strict proof, we find an interesting trade-off in deciding the number of UAVs used for jamming: jamming with more UAVs helps decrease the suspicious rate to facilitate the eavesdropping by remaining UAVs, but is at the cost of degrading the precondition of successful eavesdropping. Numerical results verify this trade-off and show that with simple one-dimensional search, the proposed jamming-assisted strategy achieves significant gain compared to conventional passive eavesdropping.

This letter investigates fairness-aware task data allocation and trajectory optimization in unmanned aerial vehicles (UAV)-assisted mobile edge computing (MEC) systems, where a fixed-wing UAV is used as a flying computing server to receive task data of mobile terminals (MTs). Under the fairness consideration, we aim to minimize the maximum energy consumption among all MTs. Despite the non-convexity of the original formulated joint optimization problem, we transform the problem into two convex sub-problems by introducing auxiliary variables, and solve them jointly by proposing an iterative algorithm. Simulation results show that the proposed algorithm can effectively reduce the maximum energy consumption among all MTs.

This letter aims to maximize the sum ergodic throughput of a power-beacon (PB)-assisted wireless powered communication network, where the PB located between several sensors and a base station (BS) first performs wireless energy transfer to the sensors and then assists forwarding the information of each sensor to the BS based on TDMA protocol. We consider the energy accumulation effect, i.e., each sensor can harvest additional energy from the PB when the PB forward the information of previous scheduled sensors, and then exhausts the accumulated energy when it starts transmission process. First, we derive the exact and approximate solutions of the ergodic throughput. Second, we prove that the optimization problem is convex and provide numerous new expressions for the optimal time allocation. Moreover, the scheduling sequence for the sensors is also optimized with two proposed methods. Simulations show the considerable gain achieved by the joint optimization scheme.

This letter studies the secrecy communication in a wireless-powered sensor network, where the access point (AP) first sends an energy signal to power the sensor node (S) and jammer (J) and, then, J exploits the harvested energy to send a jamming signal to interfere with the eavesdropper, in order to protect the uplink communication from S to the AP. Specifically, assuming that all the channels are subjected to Nakagami- $m$ fading, we derive a closed-form expression of the exact secrecy outage probability (SOP). Furthermore, by exploiting the results about the approximations to the statistics of products of independent random variables, we provide approximate and asymptotic expressions of the SOP, and the latter enables us to obtain the secrecy diversity order (SDO), observe the impact of several parameters on the SOP, and provide a closed-form expression for the time switching (TS) ratio, which maximizes the secrecy throughput. Simulations present the accuracy of the derived SOP and SDO, the tightness of the approximation, and the effectiveness of the obtained TS ratio.

This letter aims to maximize the achievable throughput of a multi-antenna-relay-assisted wireless powered communication network, where each transmission block starts with the wireless energy transfer (WET) from the energy-rich relay to the source in phase 1, follows the wireless information transmission from the source to the relay and the destination in phase 2, ends with the information forwarding from the relay to the destination in phase 3. Since that radio frequency signal can carry information and energy concurrently, WET also occurs from the relay to the source in phase 3. The closed-form expression of the optimal and suboptimal beamforming vectors at the relay in phase 3 with a fixed time split (TS) is obtained based on which the complexity of achieving the optimal TS is large. Hence, we further design a heuristic beamforming vector in phase 3, then the closed-form expression of the optimal TS is obtained, which yields near optimal performance. Moreover, the expected average throughput is analyzed.

This letter considers cooperative jamming to secure communication in the presence of multiple eavesdroppers with finite alphabet inputs. Considering the global constraint, the joint design of artificial noise covariance matrices and power allocation between the source and the relays is studied. Specifically, we transformed the problem of artificial noise design into a semi-definite programming problem, which is efficiently solved by standard optimization method. Besides, the power allocation between the source and relays is derived by utilizing the relationship between mutual information and minimum mean square error. Furthermore, a two-step algorithm is developed to enhance the achievable secrecy rate of cooperative jamming wireless network. Numerical examples demonstrate the proposed algorithm achieves a significant gain over the conventional counterparts in terms of secrecy rate.

In this letter, we investigate the distributed channel selection for interference mitigation in small cell networks considering the random deployment and dynamic on–off activity. Game theory is adopted to analyze the distributed and interactive decision making, and the problem is formulated as an exact potential game, in which the Nash equilibrium (NE) minimizes the expected network interference, either globally or locally. Furthermore, we design a fully distributed, no-regret channel selection algorithm to find the NE solution in dynamic environment.

In this letter, we investigate the partially overlapping channels for interference mitigation in dynamic and distributed networks. The interference mitigation problem is formulated as a dynamic game, which is proved to be an exact potential game. Furthermore, the performance bounds of the Nash equilibrium (NE) are theoretically derived and analyzed. Finally, we design a fully distributed, stochastic learning algorithm to converge to the NE of the formulated game. Simulation results validate the effectiveness of the proposed algorithm.

This work has studied the physical layer security in cooperative automatic-repeat-request (CARQ), under the assumption of no instantaneous channel state information (CSI) at legitimate users. Different from present works, this paper not only derives closed form expressions for connection outage probability (COP) and secrecy outage probability (SOP) to evaluate the reliability and security, respectively, but also first establishes the direct relationship between them via the reliability-security tradeoff (RST). Moreover, we present a novel formulation for secrecy throughput, which gives a more complete insight into the efficiency of CARQ achieving reliable and secure transmission.

In this letter, we study the problem of secure connectivity for colluding eavesdropper using randomize-and-forward (RF) strategy in cooperative wireless networks, where the distribution of the eavesdroppers is a homogenous Poisson point process (PPP). Considering the case of fixed relay, the exact expression for the secure connectivity probability is obtained. Then we obtain the lower bound and find that the lower bound gives accurate approximation of the exact secure connectivity probability when the eavesdropper density is small. Based on the lower bound expression, we obtain the optimal area of relay location and the approximate farthest secure distance between the source and destination for a given secure connectivity probability in the small eavesdropper density regime. Furthermore, we extend the model of fixed relay to random relay, and get the lower bound expression for the secure connectivity probability.

This work has studied the outage performance of amplify-and-forward (AF) relaying in underlay spectrum sharing systems with interference from primary user (PU). To reduce the complexity and improve the feasibility, two schemes using statistical channel state information (CSI) of interference links are proposed. For each scheme, the closed-form expressions for outage probability of secondary user (SU) and PU are derived, as well as the asymptotic expressions and diversity order. The impact of using statistical CSI instead of instantaneous CSI has been evaluated through the comparison with existing scheme. The analytical results and the simulation results are in excellent agrement confirming the effectiveness of the analysis in this work.

In this letter, we propose a distributed cooperation policy selection scheme for energy-constrained ad hoc networks. In particular, we model a correlated equilibrium (CE)-based cooperation policy selection game where the individual utility function is designed from the global energy efficiency perspective. We derive the condition under which the CE is Pareto optimal, and propose a decentralized algorithm based on the regret matching procedure that converges to the CE. The resulting CE can help us select proper cooperation policies. Simulation results demonstrate that our scheme achieves good convergence, Pareto optimality, and max-min fairness.

Space sense random access (SSRA) with collision mitigation is proposed for TDD wireless local area networks (WLANs) with multiple antennas. Before transmitting a packet, the user performs space sense to detect the status of the channel. If the channel is idle, it then transmits a common training sequence for channel estimation. Multiple subslots are available for channel estimation and the user randomly selects one subslot to achieve the possible collision-free channel estimation. It is shown that SSRA removes the requirement of orthogonal training sequences while avoiding possible packet collision and further providing multipacket reception capability. Compared to the conventional slotted ALOHA scheme, SSRA can achieve much higher throughput, as verified by extensive simulation results.