Cross-Layer Interference Management Scheme for D2D Mobile Users Using NOMA

Device-to-device (D2D) communication is one of the promising technology of the fifth-generation (5G) network. In D2D, the devices are in close proximity to each other communicate directly with or without depending upon the base station (BS), resulting in large gain, low latency, and high energy efficiency. Also, it improves the spectral efficiency by sharing the spectrum resources with cellular mobile users (CMUs). Despite these advantages, co-channel interference and eavesdropping attack on the D2D links are two major challenges. To overcome these issues, we used the power domain non orthogonal multiple access (PDNOMA) techniques with the D2D mobile groups (DMGs) under the social-domain scenario. The successive interference cancellation technique of PD-NOMA in the DMGs mitigate the intra-user and co-channel interference among the D2D receivers (DDRs), resulting in an increase in signal to interference noise ratio (SINR) and better quality of services. Furthermore, to improve the spectral efficiency, and reduce the security risk of the eavesdropper on the DMGs over each resource block (RB) in the presence of dynamic channel environment of imperfect channel state information, we used the coalition game approach. The simulated results show the proposed scheme achieves 5.5% and 27.77% higher sum rate and ensure 8.3% and 41.6% higher information secrecy as compared to first-order algorithm (FOA) and orthogonal frequency division multiple access (OFDMA) schemes.

In this paper, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Interference Reduction Scheme for Device-to-Device (D2D) Mobile Groups Using Uplink NOMA (ISHU)</i> is proposed to maximize the throughput of the network. To achieve this goal, we integrated uplink non-orthogonal multiple access (NOMA) in the D2D mobile groups (DMGs). DMGs improve the spectral efficiency by sharing the resources with cellular mobile users (CMUs) whereas, uplink NOMA in DMGs associate the large number of D2D mobile users (DMUs) with the D2D transmitter (DDT). ISHU jointly optimizes the user group association and resource allocation in the uplink NOMA-enabled DMGs. The problem of joint user association and resource allocation is formulated as a mixed integer non-linear programming. To address this problem, we divided the problem of interference mitigation in two sub-problems and solved it independently. First, for joint user group association and sub-carrier assignment, a 3-D matching game is designed between the DMUs, DDT, and sub-carriers, respectively. Second, to optimize the power of DMUs across each sub-carriers, the branch and bound (BB) technique is used. Also, to reduce the complexity of ISHU scheme, the successive convex approximation low complexity (SCALE) technique is used across each sub-carrier. Simulated results demonstrated that ISHU provides 3.846 and 26.92 percent superior throughout as compared to the existing uplink conventional NOMA and OFDMA schemes.

The fifth generation (5G) of wireless communication accompanied by the advancement of mobile internet and the Internet of Things (IoT) will create stormy data traffic. The 5G challenges like higher spectral efficiency, massive connectivity, and low latency are addressed by the Non-Orthogonal Multiple Access (NOMA) in recent years. NOMA is proven to be a promising technique from its capability to accommodate a larger number of users in contrast to the conventional orthogonal multiple access (OMA) schemes. NOMA comprises two distinct techniques such as Power-Domain NOMA and Code-Domain NOMA. The non-orthogonal resource allocation in Power-Domain NOMA is practically realized by the Superposition Coding (SC) at the Base Station (BS) and an advanced Successive Interference Cancellation at the User Equipment (UE). In this manuscript, the basic concepts of NOMA, on comparing its channel gain with OMA are discussed first. Specifically, a comprehensive survey of various SIC techniques applied under perfect and imperfect Channel State Information (CSI) uncertainties are summarized in terms of outage probability, ergodic capacity, and system performance. In addition, the sophisticated SIC techniques, when NOMA is integrated with modern wireless communication technologies such as multiple-input multiple-output (MIMO-NOMA) and Cooperative (C-NOMA) communications are investigated. Furthermore, the challenges to be solved with their corresponding opportunities and future research directions of NOMA are explored.

This study introduces a low-complexity, short-code-based strategy that combines energy harvesting for power domain non-orthogonal multiple access (PD-NOMA) techniques. Due to its non-orthogonal nature, PD-NOMA is relatively more exposed to security vulnerabilities, rapid battery depletion in users due to multi-level SIC, and significant outage probability in congested environments. The presented work uses coded cooperation and short block-length codes to make it harder for unlicensed users to manipulate or steal the data of licensed users. This makes it less likely that unlicensed users will be able to find and decode data belonging to licensed users in the NOMA system. To optimize performance and reduce the frequent outage probability in the NOMA system, we developed a novel user clustering technique. Due to multi-level successive interference cancellation (SIC) at the cell center, users’ batteries quickly drain out in congested NOMA networks, leading to their declaration as energy-constrained. To overcome this issue, we use simultaneous wireless information and power transfer (SWIPT) at user-located cell centers based on the received radio frequency signals. Furthermore, it allows cell-center users to assist cell-edge users through the coded multi-user cooperation (coded Cop-PD-NOMA) technique, thereby enhancing the base station’s (gNodeB) network coverage. During the validation process, the proposed design offers secure NOMA communication, a novel user-clustering technique, and the application of SWIPT to cooperation in the PD-NOMA infrastructure. Bit-error rate (BER) and outage probability (OP) tests show that novel user-clustering and multiuser-coded Cop-PD-NOMA outperform single-user cooperation. Simulation results show that the proposed approach significantly reduces the outage probability (OP) and improves bit-error-rate (BER) performance by approximately 6.5 dB, which is only 2.5 dB in single-user cooperation.

This article investigates using a phased linear antenna array instead of the planar array to circumvent the problem that two frequency squint steering main beams cannot cover any two beam directions simultaneously. First, we approximate the donut-shaped main beam of the linear array by means of multiple pencil-shaped main beams of a virtual planar array for matching the steering main beam of the linear array with the multi-path sparse scattering channel model mathematically and give a method for calculating the number of antenna elements of the virtual array. Second, we cope with possible inter-user interference on a single squint main beam of the linear array in some scenarios by means of the power-domain non-orthogonal multiple access (PD-NOMA) technique, making it possible to support communication with two users on a single squint main beam at the base station (BS) side. The feasible domain of PD-NOMA is given when a single antenna is used for both the BS and the user end, assuming a two-user successive interference cancellation (SIC) decoding power ratio limit. Third, three algorithms are given for serving multi-user at the BS via squint beams of the linear array. Finally, numerical results show that the second proposed algorithm supporting PD-NOMA pairing within a single donut-shaped squint main beam significantly increases the number of simultaneous users served within a single cellular system.

The rapid growth of user density and heterogeneous service requirements in 5G and emerging 6G networks has intensified multi-user interference, particularly in power-domain non-orthogonal multiple access (PD-NOMA) systems. Conventional successive interference cancellation (SIC) techniques suffer from error propagation and performance degradation under imperfect channel conditions, limiting their reliability in practical deployments. This paper proposes a deep learning–based interference cancellation framework that combines Convolutional Neural Networks (CNNs) and Bidirectional Long Short-Term Memory (BiLSTM) networks for end-to-end signal detection in downlink NOMA systems. The proposed model exploits CNN layers to extract spatial interference features from complex-valued received signals, while BiLSTM layers capture bidirectional temporal dependencies caused by channel fading and symbol correlation. Unlike traditional SIC-based receivers, DL-NOMA-CancelNet directly reconstructs user signals without explicit channel estimation or manual interference subtraction. Simulation results obtained using MATLAB under Rayleigh fading and AWGN conditions demonstrate that our framework significantly outperforms conventional Least Squares (LS), Minimum Mean Square Error (MMSE), and single-network deep learning detectors. Specifically, this method achieves up to an 8–10× reduction in bit error rate (BER) across a wide signal-to-noise ratio (SNR) range, while maintaining low inference latency and moderate model complexity. These results confirm that our work provides a robust and scalable solution for interference mitigation in future 5G/6G downlink NOMA systems, particularly for ultra-reliable low-latency communications (URLLC) and massive machine-type communications (mMTC).

To fulfill the stringent requirements brought by human-type communication (HTC) along with massive machine-type communication (MTC), device-to-device (D2D) and non-orthogonal multiple access (NOMA) techniques will inevitably be incorporated into dense cellular networks to cater massive connectivity and maintain high spectral efficiency. However, such combination may lead to very complex network topologies and bring challenge in resource allocation, interference management and transmission mode selection. Note the received signal strength (RSS) is an important factor for cellular and D2D mode selection, it can affect multi-access mode determination in D2D-aided HTC/MTC dense NOMA systems. Therefore, the RSS threshold of each cell has great impact on system performance and should be carefully tuned. To this end, we formulate the RSS-threshold selection problem as a decentralized partially observable Markov decision process to maximize the performance for downlink and uplink communications. Accordingly, we employ a multi-agent reinforcement learning based scheme wherein each small base station acts as an agent and chooses the optimal RSS threshold to achieve maximum sum rate by interacting with the environment continuously. Extensive simulation results reveal our proposed scheme can improve the system sum rate and coverage by enhancing the connectivity of massive HTC and MTC devices via D2D and NOMA techniques.

In this work, resource allocation of Cooperative Power Domain Non-Orthogonal Multiple Access (PD-NOMA) with energy harvesting technique using Multiple Input Single Output (MISO) is examined. This paper focuses on improvement of bit error rate (BER), spectral efficiency and capacity compared to conventional Non-Orthogonal Multiple Access (NOMA). Two users scenario is considered, where an user is near to the base station (BS) while the other one is far away from the base station. As both users with different power levels exist in the same spectrum, co-channel interference is inevitable. To alleviate this, an interference cancellation technique known as Successive Interference Cancellation (SIC) is used. The simulation results of cooperative NOMA with energy harvesting are compared with conventional NOMA and it can be inferred that cooperative NOMA performance is better than NOMA.

The power domain non-orthogonal multiple access (NOMA) technique introduces one of the fundamental characteristics and it exhibits the possibility of users to decode the messages of the other paired users on the same resources. In cognitive radio inspired NOMA (CR-NOMA), the base station (BS) has to serve untrusted users or users with different security clearance. This phenomenon raises a security threat particularly in such CR-NOMA. This paper develops a tractable analysis framework to evaluate the security performance of cooperative non-orthogonal multiple access (NOMA) in cognitive networks, where relay is able to serve two far NOMA users in the presence of external eavesdropper. In particular, we study the secrecy outage probability in a two-user NOMA system. This situation happens in practical the BS is pairing a legitimate user with another untrusted user. Main reason is that the non-uniform distribution in terms of trusted and untrusted users in the cell. By performing numerical results demonstrate the performance improvements of the proposed NOMA scheme in comparison to that of several situations in terms of different parameters. Furthermore, the security performance of NOMA is shown to verify the derived expressions.

This study shows how the channel estimation based Deep Learning (DL) and a power allocation method are together employed for multi-user detection in a Power domain Non-Orthogonal Multiple Access (PD-NOMA) network. Successive interference cancellation (SIC) procedure is typically employed at receiver side, where numerous users are decoded in a successive approach. Fading channels may scatter transferred signal and initiate dependencies between scattered components, this might influence the channel estimation technique and therefore impact the SIC procedure and signal recognition precision. In our proposed scheme, the influence of Deep Neural Network (DNN) in clearly approximating the channel parameters for users in NOMA cell is inspected. In our scenario, we incorporate the Long Short Term Memory (LSTM) layer with NOMA cell where the LSTM is employed for complex data management to perform training and predication. The DNN is trained online on basis of random channel models and then the trained network is used to approximate the channel taps that will be utilized by the receiver in recovering the desired symbols. Additionally, power factors for user’s devices are optimized to maximize the sum-rate of users where whole power and Quality of service (QoS) restrictions are considered. Simulation outcomes in terms of Bit Error Rate (BER), Outage probability, and sum rate have shown the dominance of the suggested channel estimation using DL over standard estimation approach. Moreover, both fixed power and optimized power schemes are also assessed when DNN is applied.

SummaryThe next generation wireless access technology highly relies on nonorthogonal multiple access (NOMA) technique. This paper proposes a novel power domain cyclic spread multiple access (PDCSMA) scheme for the design of NOMA system with power domain superposition coding (SC) and cyclic spreading at the transmitter concurrent with symbol level successive interference cancellation (SL‐SIC) at the receiver. Based on acceptable difference in channel gain, the users are grouped together to form PDCSMA clusters, and the unique power is allotted to each user in a cluster. The user with good channel condition is allotted less power, and the user with poor channel condition is allotted more power. Each PDCSMA cluster has its own spreading code, and the data of every user in a cluster are cyclic spread with the same code. Each cluster supports the number of multipath components equivalent to the length of the spreading code. The use of cyclic spreading makes the signal suffered by multipath fading less prone to intra cluster interference. The user signal is decoded by minimum mean square error‐frequency domain equalization (MMSE‐FDE) or maximal ratio combining (MRC)–based receiver in which weak user is detected with hard decision, and strong user is detected with SIC. Compared with conventional power domain NOMA (PDNOMA) and interleaved NOMA, the proposed PDCSMA achieves better bit error rate (BER) performance and assures guaranteed detection.

Gain division multiple access (GDMA) is a non-orthogonal multiple access (NOMA) technique for uplink communications. In GDMA, the receiver employs both the magnitudes and phases of channel gains associated to the users to separate users. In the power-domain NOMA, the receiver employs the power levels associated to users to separate users.We apply the GDMA concept together with orthogonal frequency division multiple access (OFDM) to combat the collision problem in the ALOHA system. Our goal is to minimize the complexity of the devices (users) required for coordination and to obtain high throughput simultaneously in the random access protocol. For the proposed unslotted OFDM-GDMA-ALOHA, each user randomly chooses a Zadoff-Chu (ZC) sequence as its preamble for the transmitted packet so that the receiver can simultaneously obtain the information for timing and the information for coarse channel estimation. Moreover, fine channel estimation is obtained by using a cluster-based method. Simulation for a coded unslotted OFDM-GDMA-ALOHA system with BPSK modulation demonstrates that the obtained throughput performance can be better than that obtained by the slotted ALOHA system without using GDMA.We also provide simulation for slotted OFDM-GDMA-ALOHA, which shows that very high throughput can be achieved if the synchronization of slots can be obtained.

Device-to-device (D2D) communication as an underlaying cellular network empowers user-driven rich multimedia applications and also has proven to be network efficient offloading eNodeB traffic. However, D2D transmitters may cause significant amount of interference to the primary cellular network when radio resources are shared between them. During the downlink (DL) phase, primary cell UE (user equipment) may suffer from interference by the D2D transmitter. On the other hand, the immobile eNodeB is the victim of interference by the D2D transmitter during the uplink (UL) phase when radio resources are allocated randomly. Such interference can be avoided otherwise diminish if radio resource allocated intelligently with the coordination from the eNodeB. In this paper, we formulate the problem of radio resource allocation to the D2D communications as a mixed integer nonlinear programming (MINLP). Such an optimization problem is notoriously hard to solve within fast scheduling period of the Long Term Evolution (LTE) network. We therefore propose an alternative greedy heuristic algorithm that can lessen interference to the primary cellular network utilizing channel gain information. We also perform extensive simulation to prove the efficacy of the proposed algorithm.

Due to the successive interference cancellation (SIC) technique, Non orthogonal multiple Access (NOMA) users have the capability of decoding the other paired users sharing the same resource bloc. As a result, NOMA technique is not only exposed to external eavesdropping, but also to internal eavesdropping which raises security risks regarding NOMA users' privacy. Therefore, this research aims to analyse a Multi-antenna cooperative NOMA system where both Decode and Forward (DF) and Amplify and Forward (AF) strategies are studied. In this context, we investigate the secrecy performance of our system with both internal and external eavesdropping scenarios. Closed-form expressions of the secrecy outage probability (SOP) and the strictly positive secrecy capacity (SPSC) metrics are derived. Numerical results are given to illustrate the validity of the obtained theoretical results.

Non-orthogonal multiple access (NOMA) is a rapidly emerging paradigm with the capability to improve the spectral efficiency of data-driven, intelligence inspired, and highly digitized sixth-generation (6G) wireless networks. In the backdrop of ever-evolving NOMA techniques, this article presents a novel resource optimization framework for maximizing the spectral efficiency (SE) of the Internet-of-things (IoT) networks using power domain NOMA. The proposed framework considers a limited number of frequency blocks in the IoT network and provides an optimal power and frequency block allocation method. Different practical constraints like successive interference cancellation (SIC) complexity, ensuring the minimum gap of received power among different IoT equipment over the same frequency block for successful SIC operation, quality of services requirements, and IoT equipment's transmit powers have also been taken into account. Accordingly, a non-convex optimization problem has been formulated for resource management where the objective of spectral efficiency is coupled by both frequency block and power allocation. To effectively solve this problem, the resource optimization problem is decoupled into two subproblems for frequency block assignment and power allocation. A suboptimal algorithm has been designed for frequency block assignment and a new optimal sequential quadratic programming (SQP) approach is employed to solve the non-convex power control subproblem. For the sake of fair comparison, a low complexity suboptimal NOMA power allocation scheme, based on Karush-Kuhn-Tucker (KKT) conditions, and conventional orthogonal multiple access (OMA) scheme are also provided. The results demonstrate that the proposed optimal resource management scheme significantly improves the system performance compared to other schemes.