Unmanned aerial vehicle (UAV) nowadays is a promising technology for boosting wireless connectivity, especially for upcoming 5G wireless networks. Due to its aerial feature, potential mobility and flexible deployment, the UAV can provide service in some specific scenarios such as post-disaster network recovery or no-infrastructure terrains. However, the problem of interference management between deployed UAV and underlaying heterogeneous networks, which guarantees the quality of service, is still a challenging task. In this paper, we address the outage probability for UAV connected users and device-to-device (D2D) receivers simultaneously operating in D2D underlaying NOMA UAV-assisted networks, and we derive its closed-form expressions, which turns out to be very accurate. We also solve the power control optimization problem via relaxing the non-convex problem into solving successive low-complexity linear programs to obtain a sub-optimal solution to the problem. The simulation results in confirm the superiority of the proposed approach in the terms of computational complexity and its compromise in the terms of sum rate. INDEX TERMS UAV, outage probability, power control, D2D, NOMA.
The deployment of femtocells in current and future communication systems promises an effective solution for limited indoor coverage problem and a possible gateway for mobile data offloading. In this paper, we cast a cognitive interference align ment approach (IA) suitable for heterogeneous cellular networks with a mixed macrocell and femtocell deployment Specifically, in our approach a restricted waterfflling (RWF) algorithm is used to maximize the downlink data rate, while reserving some eigenmodes for giving the femtocell basestations the opportunity to do their transmissions even at high signal-to-noise power ratio (SNR) for the macrocell basestation. Additionally, both the cross-tier and co-tier interference is to be aligned at each femtocell user's receiver using an Iterative Reweighted Least Squares(IRLS) algorithm. The simulation results show that the proposed IA approach provides an improved sum rate for the femtocell users, compared to the conventional IA techniques, Uke, the leakage minimization approach and the nuclear norm based rank constraint rank minimization approach.
Increasing demand for higher data-rate wireless connectivity with lower latency is fueling the explorations of millimeter-wave (mmWave) spectrum and massive MIMO communications. Both technologies are recognized as the key enablers of 5G and beyond 5G (B5G) networks. Hybrid beamforming is one of the most promising energy and cost-effective approaches to realize mmWave massive MIMO communications with lower complexity and smaller training overhead. With the motivation of giving more insights and in-deep technical recommendations to B5G network designers regarding hybrid beamforming, we present a hybrid beamforming taxonomy in terms of channel state information (CSI) availability, frequency bandwidth, architecture complexity, analog beamformer components, number of users, connectivity to RF chains, and the digital and analog beamforming design. Furthermore, we provide a comprehensive survey on the state-of-the-art use-cases for each classification followed by identification of the future challenges and open research issues. INDEX TERMS Hybrid beamforming (HBF), energy efficiency (EE), millimeter wave (mmWave), hardware complexity, massive-MIMO, analog beamforming (ABF), and digital beamforming (DBF).
Due to the increasingly complicated communication scenarios and network architectures as well as growing traffic demands for high speed connectivity, dynamic spectrum allocation in fifth generation (5G) networks becomes insufficient to guarantee the satisfaction of main network requirements in terms of spectrum efficiency (SE), scalability, delay, and energy efficiency (EE). Enormous multiple access schemes and cognitive radio (CR) network scenarios come to fulfill these requirements and enhance network functionalities. With multiple access schemes, users are able to transmit their data streams simultaneously under maximum capacity constraints. On the other hand, vacant spectrum holes are exploited in an opportunistic manner via CR and software defined radio. In order to exploit these spectrum holes as well as meeting different network requirements, several multiple access techniques have been presented that have been initiated through the adoption of orthogonal multiple access (OMA) scheme. Additionally, non-orthogonal multiple access (NOMA) and space division multiple access (SDMA) are presented to achieve a promising multiplexing gain as well as to address the inefficient spectrum utilization incurred with OMA schemes. However, such multiplexing gain is limited as it depend on the channel conditions. Accordingly, a generalized multiple access scheme has been presented recently, namely rate splitting multiple access (RSMA), to further enhance the SE. In this paper, we provide a comprehensive study regarding the key multiple access schemes presented for CRNs to further enhance the use of spectral resources, and additionally highlights the key implementation challenges and the enabling techniques addressed to overcome it. We have given a special attention to the enhances provided by RSMA as compared with OMA, SDMA, and NOMA techniques. Finally, some open issues are spotted to shed lights on the need for further studies and future research efforts.INDEX TERMS Multiple access, SDMA, NOMA, RSMA, cognitive radio (CR), 5G.
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