In this paper, the capacity improvement of full-duplex (FD) device-to-device (D2D) underlaying cellular networks (CNs) is analyzed. A single-cell environment is considered with one half-duplex (HD) base station, multiple HD cellular user equipments (CUEs), and one pair of FD D2D user equipments (DUEs). The BS is equipped with M multiple antennas, and one pair of FD DUEs is permitted to share the same resource with M out of K uplink HD CUEs, which will lead to a more complex interference environment. First, a novel interference-limited area-based (ILA-based) scheme is proposed to manage the co-channel interference from CN CUEs to FD DUEs. The ILA-based scheme does not allow the coexistence of HD CUEs and FD DUEs if the HD CUEs are located in any region of the two ILAs. Next, a senior ILA-based (SILA-based) scheme is proposed to reduce the complexity of the ILA-based scheme, in which only a common ILA is designed for both FD DUEs instead of the two ILAs in the ILA-based scheme. Then, the lower bounds of the ergodic capacity for FD D2D communications with imperfect self-interference cancellation (SIC) are derived in closed-forms with the ILA-based scheme and the SILA-based scheme. Furthermore, the capacity gain of the FD D2D communications is analyzed, and the numerical results show that the capacity improvement of the FD D2D communications is much greater than the traditional HD D2D communication if the sufficient SIC is achieved.

In wireless rechargeable sensor networks for mobile multimedia services, the multi-hop transmission method is often used to reduce the distance of a single hop to save energy. However, the sensor nodes in special locations always carry more forwarding load,which causes energy holes. These sensor nodes in energy hole have the higher energy consumption and the less residual energy, which makes them very fragile and easy to exhaust energy. If a sensor node dies, the structure of the network will be changed and the original function will be affected. In this paper, an energy-balanced joint routing and charging framework is proposed to balance the energy consumption between sensors. By analyzing the network model, the proposed framework is decomposed into a routing strategy and a charging strategy. Considering the impact of the routing structure on sensors energy consumption, the goal of the routing strategy is designed to optimize the routing tree corresponding to the mobile charger staying at each sensor node. Furthermore, the proposed charging strategy prefers the charging path with the best balance of the total energy consumption of sensor nodes during one charging trip. In order to solve these optimization problems, the simulated annealing algorithms, including the proposed random solution generation method and acceptance rules, are used to obtain a fast convergence. The simulation results show that the proposed joint routing and charging framework has better energy balance performance than the traditional scheme.

With the advent of 5G, multimedia services in wireless communication networks will grow dramatically. So far, many researches have focused on improving security,throughput and channel capacity to support multimedia services. In this paper, a new system model of full-duplex (FD) two-way amplify-and-forward (AF) relay network with simultaneous wireless information and power transfer is presented, where two FD legitimate nodes with two single-antenna communicate with each other via energy-constrained AF relay with multiple antennas, and there is a half-duplex node with single antenna who intends to eavesdrop. This paper targets to maximize the secrecy sum rate of the system by designing the transmit beamforming vector of relay under power constraint and zero-forcing constraint, where two energy harvesting protocols, namely, power splitting and time switching are considered. However the maximization problem is a non-convex optimization, and it is very complex to solve. Therefore a linear method is used to find the lower bound of the secrecy sum rate and the non-convex problem is transformed into a convex optimization problem. After that, an iterative algorithm based on difference-of-convex programming is proposed to solve this convex optimization problem. The simulation results show the good convergence of the proposed iterative algorithm and also the superiority of secrecy sum rate of our proposed scheme compared with two traditional schemes.

Device-to-device (D2D) communication allows direct device interactions but is limited by signal attenuation, interference, and energy constraints. Integrating intelligent reflecting surfaces (IRSs) and wireless-powered communication networks (WPCNs) enhances signal propagation and supports energy harvesting (EH). This letter proposes a new framework to maximize system throughput in IRS-aided D2D communication, dividing operations into EH and D2D communication stages. An alternating iterative algorithm is employed to jointly optimize the EH duration and the IRS phase shifts for both stages. Sequential quadratic programming (SQP) is utilized to determine the optimal duration of EH, while the phase shift optimization in both stages is achieved through Lagrangian dual transformation, fractional programming, and semidefinite relaxation (SDR). Simulation results validate the proposed approach by demonstrating significant throughput improvements compared to the prior art.

Data traffic has grown exponentially with the rapid development of narrowband Internet of Things (NB-IoT) technology. Non-orthogonal multiple access (NOMA) and mobile edge computing (MEC) are essential technologies to enhance the performance of NB-IoT networks. This paper proposes a new hybrid NOMA offloading strategy, allowing an IoT device to execute NOMA with other devices at different periods until the task offloading is completed. An optimization problem is established to minimize the overall offloading delay. To find the solution to the problem, we first use the proposed offloading strategy to determine the pairing method and offloading order of the IoT devices. Then, we transform the delay optimization problem into the link rate maximization problem. Finally, the closed-form solution of the optimal power allocation scheme for each IoT device is derived according to the theoretical analysis and the Karush-Kuhn-Tucker (KKT) condition. The simulation results show that the proposed offloading strategy and power allocation scheme effectively reduce the overall offloading delay under different device numbers and data lengths, which exceeds the orthogonal multiple access (OMA) schemes, the pure NOMA scheme, and the iterative multi-user NOMA scheme in lowering offloading delay

Full-duplex (FD), Device-to-Device (D2D) and non-orthogonal multiple access (NOMA) are promising wireless communication techniques to improve the utilization of spectrum resources. Meanwhile, introducing FD, D2D and NOMA in cellular networks is very challenging due to the complex interference problem. To deal with the complex interference of FD D2D underlaying NOMA cellular networks, power allocation (PA) is extensively studied as an efficient interference management technique. However, most of the previous research works on PA to optimize energy efficiency only consider the system framework of partially joint combining techniques of FD, D2D and NOMA, and the constraints of optimization problem are very different. In this paper, in order to further improve the energy efficiency of a system, a dual-layer iteration power allocation algorithm is proposed to eliminate the complex interference. The outer-layer iteration is to solve the non-linear fractional objective function based on Dinkelbach, and the inner-layer iteration is to solve the non-convex optimization problem based on D.C. programming. Then, the non-convex and non-linear fractional objective function is transformed into a convex function to solve the optimal power allocation. In this approach, FD D2D users reuse the spectrum with downlink NOMA cellular users. Imperfect self-interference (SI) cancellation at the FD D2D users and the successive interference cancellation (SIC) at the strong NOMA user are considered in the system framework. The optimization problem is constructed to maximize the system’s energy efficiency with the constraints of successful SIC, QoS requirements, the maximum transmit power of BS and FD D2D users. Numerical results demonstrate that the proposed algorithm outperforms the traditional orthogonal multiple access (OMA) in terms of energy efficiency with a higher system sum rate.