This survey provides a comprehensive overview of Cooperative non orthogonal multiple access (C-NOMA) systems, where cooperative relaying enhances reliability, extends coverage, and strengthens system robustness. The study begins by classifying the fundamental structures of C-NOMA into two key categories: user-assisted relaying, where end-user devices forward information to other users, and dedicated relaying, where separate relay nodes assist transmission. Beyond its basic principles, the survey explores the integration of C-NOMA with advanced technologies such as cognitive radio (CR), full-duplex (FD) transmission, simultaneous wireless information and power transfer (SWIPT), power line communication (PLC), multiple-input multiple-output (MIMO), heterogeneous networks (HetNets), rate-splitting multiple access (RSMA), visible light communication (VLC), and intelligent reflecting surfaces (IRS). These integrations significantly improve energy efficiency, spectral utilization, and coverage reliability. Moreover, artificial intelligence (AI), including deep reinforcement learning (DRL) and federated learning (FL), is identified as a vital enabler for intelligent power allocation, relay selection, and user clustering, addressing the limitations of traditional optimization approaches. This survey elaborates in detail the integration of C-NOMA with blockchain, edge computing, quantum computing, extended reality (XR) i.e., virtual reality/augmented reality (VR/AR), and unmanned aerial vehicles (UAV). Furthermore, this survey identifies quantum-enabled C-NOMA as a transformative paradigm, where quantum key distribution (QKD) ensures physical layer security (PLS), and quantum machine learning (QML) enhances interference mitigation and large-scale optimization. Performance evaluation in terms of spectral efficiency (SE), energy efficiency, and quality-of-service (QoS) requirements is critically analyzed, with special emphasis on challenges such as accurate channel state information (CSI) acquisition, robust successive interference cancellation (SIC), scalable relay selection, and security in heterogeneous environments. In summary, this survey consolidates the state-of-the-art developments in C-NOMA and outlines future research directions, including AI-driven optimization, quantum-assisted communication, UAV and satellite integration, reconfigurable intelligent surface (RIS)-enabled designs, and hybrid OMA-NOMA switching. By addressing these open challenges, C-NOMA is expected to serve as a cornerstone for secure, energy-efficient, and ultra-reliable connectivity in 6G and beyond, enabling massive IoT, autonomous systems, and next-generation smart city infrastructures.

The advancement in quantum computing has led to a significant progress in the development of public-key cryptosystems, referred as Post Quantum Cryptography (PQC) which has robust security to withstand both classical and quantum attacks. Lattice-based cryptography, one of the most promising PQC candidate offers low complexity and has strong security proof relying on the hardness of Learning-with-errors (LWE) problem. A variant of LWE, Ring-learning-with-error (RLWE) performs arithmetic operations over a polynomial ring and has more efficient implementations compared to LWE. Recent works propose Binary-ring-learning-with-error (BRLWE), a new variant of RLWE which has less key size and more efficient implementations compared to both LWE and RLWE-based schemes. In this paper, an algorithm is developed for BRLWE-based scheme based on decomposing the arithmetic operation $H.L\; mod (x^{n}+1) + M$ into desired number of segments. The arithmetic operation includes polynomial multiplication and addition over the ring $x^{n}+1$ where H and M are two integer polynomials and L is a binary polynomial. We illustrate two efficient hardware architectures Dual-LFSR (DL) and Quad-LFSR (QL) to enable parallel execution of individual segments employing LFSR structures to have a significant reduction in latency compared to the existing works. Despite of having larger area, the reduction in latency leads to an improvement in other performance metrics such as delay, Area-Delay Product (ADP), Power-Delay Product (PDP), throughput and efficiency making the proposed structures well suitable for PQC schemes. Experimental results show that the proposed architectures when compared with the recently reported work has 23% and 25% ADP improvement with DL and QL structures respectively when n = 256.