This work investigates the performance of an Index Modulation-aided Non-Orthogonal Multiple Access (IM-NOMA) scheme in Simultaneously Transmitting and Reflecting Reconfigurable Intelligent Surface (STAR-RIS)-assisted wireless networks. In the proposed system, information intended for a specific index-modulated (IM) user is conveyed via spatial modulation across STAR-RIS subsurfaces, where active indices are selected according to a predefined mapping. The IM user employs an energy-based maximum likelihood (EML) detector to infer the transmitted indices by exploiting the energy variations in the received signal. Alongside the IM user, additional users are multiplexed using conventional NOMA techniques, resulting in a hybrid IM-NOMA system. We focus on analyzing the conditional pairwise error probability (PEP) to characterize the system’s bit error rate (BER) performance. A union bound on the BER is derived using the PEP expression over Beaulieu-Xie (BX) fading channels. The resulting analysis provides tractable insights into the system behavior under practical propagation conditions. Extensive Monte Carlo simulations support the analytical findings, confirming the validity of the PEP-based union bound for evaluating the performance proposed IM-NOMA scheme in STAR-RIS environments.

The present contribution investigates Index Modulation Aided Non-Orthogonal Multiple Access (IM-NOMA) in simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RIS)-assisted networks. In the proposed IM-NOMA scheme, the information for a specific user (IM user) is spatially modulated across STAR-RIS subsurfaces according to a predefined pattern. Then, the IM user detects its signal using an energy-based maximum likelihood (EML) detection method, which technically leverages the energy of the received signals to identify the active subsurface indices. In this context, the performance of the proposed IM-NOMA scheme is quantified over Beaulieu-Xie (BX) fading channels in terms of pairwise error probability (PEP), bit error rate union bound, and achievable rate. The obtained PEP expressions are then used to derive a tight upper bound on the bit error rate (BER), which is subsequently utilized in quantifying the overall system performance in terms of upper-bound BER and the achievable rate. Finally, we validate the derived analytic expressions with respective results from extensive Monte Carlo simulations that provide valuable insights of the theoretical and practical importance on the achievable performance for all users in the system.

Integrating Cognitive Radio (CR) technology in Internet-of-Things (IoT) devices allows efficient large-scale deployment of IoT systems. Recently, research efforts are shifted toward adopting CR in IoT as a response for the spectrum scarcity problem. Unfortunately, CR Networks (CRNs) share the same security weaknesses with traditional wireless networks. CR communication is also vulnerable to jamming attacks which can significantly affect network performance, consume network resources and results in delays, that make it less suitable for IoT time-critical systems. Routing in CR-based IoT networks, in general, considered as a challenging issue. Under the jamming attack, routing becomes even more challenging. In this paper, we introduce a new jamming-aware routing and channel assignment protocol that deals with proactive jamming attacks in CR-based IoT networks without requiring extra resources. The proposed protocol attempts at improving the overall packet delivery ratio in the network while considering the primary user's activities, multi-channel fading and jamming behavior. The proposed protocol consists of three phases: route discovery, channel assignment, and path selection. The channel assignment problem along each path is formulated as an optimization problem with the objective of maximizing the end-to-end probability of success. This problem is shown to be an uni-modular problem, which can be solved in polynomial-time using linear programming techniques. Compared to reference protocols, simulation results reveal that the proposed protocol significantly improves network performance in terms of packet delivery ratio.