The Device-to-device (D2D) networks bear a close resemblance to future Internet of Things (IoT) networks. Resource management is an important aspect for realization of D2D communication in upcoming IoT networks. In this paper, we select underlay in-band D2D communication as it is more beneficial in terms of spectral efficiency even though it comes at the cost of interference with cellular communication. To deal with this difficulty, we propose a novel downlink resource sharing strategy, where multiple D2D users (D2Ds) share the resource of a single cellular user (CU), and each D2D pair reuses multiple channels from different cellular users (CUs). The proposed scheme adopts a channel selection technique, wherein multiple channels of CU can be shared by each D2D user. Furthermore, optimal power for each D2D user is determined through the Lagrangian dual optimization method. The formulated power control maximization scheme nicely balances the total transmission power of D2D and D2D sum-rate. The proposed channel and power allocation problem aims at maximizing the D2D sum-rate by increasing the number of active D2D links while preserving the quality of service (QoS) of CU. Finally, a relationship between energy efficiency (EE) and transmit power of D2D is investigated through an EE maximization problem. The overall system performance is evaluated in terms of the D2D shared ratio, throughput gain of the network, and computational complexity of the proposed optimal strategy. Further, the merits of using the proposed resource sharing scheme over the existing schemes are also verified through numerical results.

The device-to-device (D2D) networks bear a close resemblance to future Internet-of-Things (IoT) networks. IoT plays a significant role in the FinTech industry, especially in data security and context-aware applications. D2D communication in cellular networks has emerged as a competent technology for the upcoming future cellular networks. To improve spectral efficiency and data secrecy, we propose a two-phase network coding-based two-way decode-and-forward (DF) relaying policy for D2D communication. First, a suitable relay node is selected considering the end-to-end signal-to-interference-plus-noise ratio (SINR). Then, an XOR-based DF operation is performed when the signal transmitted by both the D2D users (DUEs) is successfully decoded at the relay node. In order to analyze the performance of the proposed two-way communication system, we derive the outage probability expression as a function of various system parameters, such as the SINR, position of both the relays and DUEs, power splitting factor, number of relays, and data rate. Furthermore, we also derive an expression for the error probability and average throughput of the D2D link to evaluate a fair comparison of the proposed approach with the traditional methods. The analytical results are also validated with the simulation results to justify the efficacy of the proposed method.

Vehicle-to-Everything (V2X) communication plays a vital role in Internet of Things (IoT)-driven intelligent transportation systems (ITS), enabling the real-time exchange of information among vehicles, infrastructure, and networks. To address the increasing demands for capacity, reliability, and latency in dense vehicular environments, this paper investigates an efficient power and resource allocation framework for NOMA-enabled V2X communication to maximise the energy efficiency (EE) of the system, while maintaining the QoS of vehicular groups (VGs) and Vehicle-to-Infrastructure (V2I) users. To achieve this, we divide the problem into three sub-problems and employ the Dinkelbach technique to solve the EE optimisation. The Concave-Convex Procedure (CCCP) and Lagrange Multiplier technique are used to find the optimal power of VGs and V2I users. A weighted bipartite matching algorithm is used for the spectrum reuse matching problem. Furthermore, the computational complexity of the proposed algorithm is analysed to assess its practical feasibility. The system performance is evaluated in terms of EE under varying path loss exponents, VG transmit power levels, and the number of VGs. System fairness is evaluated in terms of Jain’s Fairness Index (JFI). The simulation results show that the proposed scheme improves in terms of EE while ensuring that the QoS requirements of both VGs and V2I users are met. The proposed scheme is also compared with existing schemes in terms of EE.