To cope with the explosive traffic growth expected in next-generation wireless networks, it is necessary to design next-generation multiple access techniques that can provide higher spectral efficiency as well as larger-scale connectivity. As a promising candidate, power-domain non-orthogonal multiple access (NOMA) has been widely studied. In conventional power-domain NOMA, multiple users are multiplexed in the same time and frequency band with different preset power levels, which, however, may limit the spectral efficiency under practical finite alphabet inputs. Inspired by the concept of spatial modulation, we propose to solve this problem by encoding extra information bits into the power levels, and exploiting different signal constellations to help the receiver distinguish between them. To convey this idea, termed power selection (PS)-NOMA, clearly, we consider a simple downlink two-user NOMA system with finite input constellations. Assuming maximum-likelihood detection, we derive closed-form approximate bit error rate (BER) expressions for both users. Moreover, the two-user achievable rate region is also characterized. Simulation results verify the analysis and show that the proposed PS-NOMA can outperform conventional NOMA in terms of BER and achievable rate.

Edge caching can effectively reduce backhaul burden at core network and increase quality-of-service at wireless edge nodes. However, the beneficial role of edge caching cannot be fully realized when the offloading link is in deep fade. Fortunately, the impairments induced by wireless propagation environments could be renovated by a reconfigurable intelligent surface (RIS). In this paper, a new RIS-aided edge caching system is proposed, where a network cost minimization problem is formulated to optimize content placement at cache units, active beamforming at base station and passive phase shifting at RIS. After decoupling the content placement subproblem with the hybrid beamforming design, we propose an alternating optimization algorithm to tackle the active beamforming and passive phase shifting. For active beamforming, we transfer the problem into a semidefinite programming (SDP) and prove that the optimal solution of SDP is always rank-one. For passive phase shifting, we introduce the block coordinate descent method to alternately optimize the auxiliary variables and the RIS phase shifts. Further, a conjugate gradient algorithm based on manifold optimization is proposed to deal with the non-convex unit-modulus constraints. Numerical results show that our RIS-aided edge caching design can effectively decrease the network cost by improving the quality of offloading links.

The ever-increasing requests of users in emergency communication scenarios lead to high data traffic and transmission delay, posing challenges for resource-limited space-air-ground integrated networks (SAGINs). To address this issue, this paper proposes a joint caching optimization and user selection (JCOUS) problem that leverages unmanned aerial vehicle (UAV) caching to maximize the residual energy of the satellite, considering the limited resources of UAVs. To address the complex time-coupling optimization problem with discrete variables, we propose a primal decomposition method to decouple the problem, and design an energy-efficient user selection algorithm with dynamic caching. Furthermore, to reduce computational complexity and cost, we consider a statistical scenario and maximize the statistical residual energy in the JCOUS problem. Simulation results verify that the proposed scheme can achieve a higher residual energy and fast optimization, thus realizing energy saving and quick decision making especially in large-scale computation-intensive SAGINs.

Nowadays, intelligent transportation industry is becoming a hot spot in Internet of vehicles (IoV). However, owing to the existence of numerous intelligent terminals, communication security becomes a pressing problem. On the other hand, pervasive edge computing (PEC), as a pivotal technology, can significantly improve the performance of the system compared to the traditional cloud computing. In this paper, we propose a non-orthogonal multiple access (NOMA)-based PEC power allocation framework in IoV, aiming at minimizing the system latency in the presence of eavesdroppers. Besides, queuing models, imperfect channel state information, and vehicles' speeds are all considered. Since the formulated problem is complicated, we consider its lower bound and derive the sub-optimal closed-form expressions of the power allocation coefficients. Furthermore, a frank-and-wold algorithm is proposed to achieve the optimum total power. Simulation results illustrate the superior performance of the proposed NOMA scheme.

In this paper, a multi-vehicle multi-task non-orthogonal multiple access (NOMA) assisted mobile edge computing (MEC) system with passive eavesdropping vehicles is investigated. To heighten the performances of edge vehicles, we propose a vehicle grouping pairing method, which utilizes vehicles near the MEC to assist edge vehicles as full-duplex relays. For promoting transmission security, we employ artificial noise to interrupt eavesdropping vehicles. Furthermore, we derive the approximate expression of the secrecy outage probability of the system. The combined optimization of vehicle task division, power allocation, and transmit beamforming is formulated to minimize the total delay of task completion for edge vehicles. Then, we design a power allocation and task scheduling algorithm based on the genetic algorithm to solve the mixed-integer non-linear programming problem. Numerical results demonstrate the superiority of our proposed scheme in terms of system security and transmission delay.

Radio FD has emerged as an attractive technique capable of doubling the spectral efficiency over half duplex. However, for signal reception, an FD node needs to suppress its transmitter's signals quite significantly. In point to point communication systems, these transmitter signals are termed self-interference. When working with an FD mobile network, the self-interference problem becomes much more complicated because the receiver of an FD base station (BS) receives interference not only from its BS transmitter in its cell, but also from those in the surrounding cells. For the UL channel, self-interference extends to the problem of multiple interference. And, a similar interference problem can be found among the MSs over a DL channel. In both cases, the interference owing to the FD implementation spreads beyond the scope of the self-interference. This article describes the development of FD BSs that use antenna arrays to deal with the BSs' interference, and thus enable FD communication over the UL channel, where the theoretical focus is placed on how to use the antenna array to nullify the multiple interference and receive the signals of the desired MSs simultaneously. To complete the system construction, FD MSs have also been developed to enable DL transmission. A prototype system is described for the scenario of two cells and one FD MS for tests of FD communication over UL channels and DL channels in terms of video performance. Good video quality is demonstrated at both the BS and MS.