Low-complexity Resource Allocation for User Paired RSMA in Future 6G Wireless Networks

Rate-splitting multiple access (RSMA) uplink requires optimization of decoding order and power allocation, while decoding order is a discrete variable, and it is very complex to find the optimal decoding order if the number of users is large enough. This letter proposes a low-complexity user pairing-based resource allocation algorithm with the objective of minimizing the maximum latency, which significantly reduces the computational complexity and also achieves similar performance to unpaired uplink RSMA. A closed-form expression for power and bandwidth allocation is first derived, and then a bisection method is used to determine the optimal resource allocation. Finally, the proposed algorithm is compared with unpaired RSMA, paired NOMA and unpaired NOMA. The results demonstrate the effectiveness of the proposed algorithm

Routing Protocols for Underwater Acoustic Sensor Networks: A Survey from an Application Perspective

Underwater acoustic communications are different from terrestrial radio communications; acoustic channel is asymmetric and has large and variable end‐to‐end propagation delays, distance‐dependent limited bandwidth, high bit error rates, and multi‐path fading. Besides, nodes’ mobility and limited battery power also cause problems for networking protocol design. Among them, routing in underwater acoustic networks is a challenging task, and many protocols have been proposed. In this chapter, we first classify the routing protocols according to application scenarios, which are classified according to the number of sinks that an underwater acoustic sensor network (UASN) may use, namely single‐sink, multi‐sink, and no‐sink. We review some typical routing strategies proposed for these application scenarios, such as cross‐layer and reinforcement learning as well as opportunistic routing. Finally, some remaining key issues are highlighted

Integrating millimeter wave with hybrid precoding multiuser massive MIMO for 5G communication

Nowadays, there has been growing interest in the Massive MIMO as a result of improving throughput by leveraging spatial freedom and array gain. It is equipped with millimeter wave (mm Wave) bands to resolve the high path-loss. It is known from the literature that iterated algorithms are usually used to attain the hybrid precoders to accomplish a specific optimization objective. Thus, the complexity remains high because each iteration may include singular value decomposition, the matrix inversion, and so on that motivates us to split the hybrid precoding and combining problem into sub-problems. The proposed solution is a multi-user Massive MIMO hybrid beamforming based on a convex optimization problem that is applied and solved for estimating the digital precoding to eliminate inter-user interference while using codebooks to select analog beamformers. It is apparent in the majority of cases; the proposed beamforming performance is higher than only-analog beamforming, single-user (no interference), the ZF precoding, the MMSE precoding, and the Kalman precoding where the full digital solution is a considerable as the benchmark point with different scenarios due to the reduction of user interference. Thus, there is no consideration for complicated operations such as SVD or inversion matrices as well as no need for data estimation. Our proposed solution can serve a large number of users simultaneously due to more directive gain by using numerous antennas at BS. Based on its less complexity and keeping performance, our solution can be recommended

Energy efficient hybrid satellite terrestrial 5G networks with software defined features

In order to improve the manageability and adaptability of future 5G wireless networks, the software orchestration mechanism, named software defined networking (SDN) with Control and User plane (C/U-plane) decoupling, has become one of the most promising key techniques. Based on these features, the hybrid satellite terrestrial network is expected to support flexible and customized resource scheduling for both massive machinetype- communication (MTC) and high-quality multimedia requests while achieving broader global coverage, larger capacity and lower power consumption. In this paper, an end-to-end hybrid satellite terrestrial network is proposed and the performance metrics, e. g., coverage probability, spectral and energy efficiency (SE and EE), are analysed in both sparse networks and ultra-dense networks. The fundamental relationship between SE and EE is investigated, considering the overhead costs, fronthaul of the gateway (GW), density of small cells (SCs) and multiple quality-ofservice (QoS) requirements. Numerical results show that compared with current LTE networks, the hybrid system with C/U split can achieve approximately 40% and 80% EE improvement in sparse and ultra-dense networks respectively, and greatly enhance the coverage. Various resource management schemes, bandwidth allocation methods, and on-off approaches are compared, and the applications of the satellite in future 5G networks with software defined features are proposed