NOMA-Enabled Optimization Framework for Next-Generation Small-Cell IoV Networks Under Imperfect SIC Decoding

in IEEE Transactions on Intelligent Transportation Systems (2022)

To meet the demands of massive connections, diverse quality of services (QoS), ultra-reliable and low latency in the future sixth-generation (6G) Internet-of-vehicle (IoV) communications, we propose non ... [more ▼]

To meet the demands of massive connections, diverse quality of services (QoS), ultra-reliable and low latency in the future sixth-generation (6G) Internet-of-vehicle (IoV) communications, we propose non-orthogonal multiple access (NOMA)-enabled small-cell IoV network (SVNet). We aim to investigate the trade-off between system capacity and energy efficiency through a joint power optimization framework. In particular, we formulate a nonlinear multi-objective optimization problem under imperfect successive interference cancellation (SIC) detecting. Thus, the objective is to simultaneously maximize the sum-capacity and minimize the total transmit power of NOMA-enabled SVNet subject to individual IoV QoS, maximum transmit power and efficient signal detecting. To solve the nonlinear problem, we first exploit a weighted-sum method to handle the multi-objective optimization and then adopt a new iterative Sequential Quadratic Programming (SQP)-based approach to obtain the optimal solution. The proposed optimization framework is compared with Karush-Kuhn-Tucker (KKT)-based NOMA framework, average power NOMA framework, and conventional OMA framework. Monte Carlo simulation results unveil the validness of our derivations. The presented results also show the superiority of the proposed optimization framework over other benchmark frameworks in terms of system sum-capacity and total energy efficiency. [less ▲]

Energy Efficiency Optimization for Backscatter Enhanced NOMA Cooperative V2X Communications under Imperfect CSI

in IEEE Transactions on Intelligent Transportation Systems (2022)

Automotive-Industry 5.0 will use beyond fifth-generation (B5G) technologies to provide robust, computationally intelligent, and energy-efficient data sharing among various onboard sensors, vehicles, and ... [more ▼]

Automotive-Industry 5.0 will use beyond fifth-generation (B5G) technologies to provide robust, computationally intelligent, and energy-efficient data sharing among various onboard sensors, vehicles, and other devices. Recently, ambient backscatter communications (AmBC) have gained significant interest in the research community for providing battery-free communications. AmBC can modulate useful data and reflect it towards near devices using the energy and frequency of existing RF signals. However, obtaining channel state information (CSI) for AmBC systems would be very challenging due to no pilot sequences and limited power. As one of the latest members of multiple access technology, non-orthogonal multiple access (NOMA) has emerged as a promising solution for connecting large-scale devices over the same spectral resources in B5G wireless networks. Under imperfect CSI, this paper provides a new optimization framework for energy-efficient transmission in AmBC enhanced NOMA cooperative vehicle-to-everything (V2X) networks. We simultaneously minimize the total transmit power of the V2X network by optimizing the power allocation at BS and reflection coefficient at backscatter sensors while guaranteeing the individual quality of services. The problem of total power minimization is formulated as non-convex optimization and coupled on multiple variables, making it complex and challenging. Therefore, we first decouple the original problem into two sub-problems and convert the nonlinear rate constraints into linear constraints. Then, we adopt the iterative sub-gradient method to obtain an efficient solution. For comparison, we also present a conventional NOMA cooperative V2X network without AmBC. Simulation results show the benefits of our proposed AmBC enhanced NOMA cooperative V2X network in terms of total achievable energy efficiency. [less ▲]

An Enhanced Spectrum Reservation Framework for Heterogeneous Users in CR-Enabled IoT Networks

in IEEE Wireless Communications Letters (2021)

Fulfilling the diverse communication requirements of heterogeneous users is envisioned to be one of the key challenges in cognitive radio-enabled IoT networks. To this end, we propose a novel scheme ... [more ▼]

Fulfilling the diverse communication requirements of heterogeneous users is envisioned to be one of the key challenges in cognitive radio-enabled IoT networks. To this end, we propose a novel scheme focused on multi-tier prioritized and heterogeneous regime of users and reservation-based resources allocation. The proposed scheme manipulates the secondary users’ (SUs’) heterogeneity based on their priorities for improving their capacities and blocking probabilities. Besides, the scheme systematically deals with SUs’ dropping for bringing fairness in the service provisioning to SUs. Furthermore, the scheme allows primary users (PUs) to follow an organized approach when accessing channels for mitigating the number of handoffs. Additionally, we propose a dynamic channel reservation algorithm for PUs to enhance spectrum utilization. We leverage the continuous-time Markov chain for system modeling and consider channel failures for making the analysis more realistic. Results confirm the effectiveness of our scheme as compared to the state-of-the-art. [less ▲]