Downlink Non-orthogonal Multiple Access System Research Articles

Dynamic Power Allocation for Downlink NOMA

Dynamic Power Allocation for Downlink Non-Orthogonal Multiple Access (NOMA) is a critical research area in wireless communication systems. This study focuses on implementing and evaluating dynamic power allocation strategies in the context of downlink NOMA. We compare the performance of dynamic power allocation with fixed power allocation schemes to assess their impact on system throughput, interference management, and overall efficiency. Through extensive simulations and analysis in this paper using MATLAB, we demonstrate a comparison between dynamic power allocation and fixed power allocation, and the advantages of dynamic power allocation in adapting to changing channel conditions and user requirements, leading to improved system performance. Our results show the data rate and outage probability which provides valuable insights into the benefits of dynamic power allocation in downlink NOMA systems and highlight the importance of adaptive power management techniques in enhancing wireless communication networks.

Optimal Decoding Order and Power Allocation for Sum Throughput Maximization in Downlink NOMA Systems.

In this paper, we consider a downlink non-orthogonal multiple access (NOMA) system over Nakagami-m channels. The single-antenna base station serves two single-antenna NOMA users based on statistical channel state information (CSI). We derive the closed-form expression of the exact outage probability under a given decoding order, and we also deduce the asymptotic outage probability and diversity order in a high-SNR regime. Then, we analyze all the possible power allocation ranges and theoretically prove the optimal power allocation range under the corresponding decoding order. The demarcation points of the optimal power allocation ranges are affected by target data rates and total power, without an effect from the CSI. In particular, the values of the demarcation points are proportional to the total power. Furthermore, we formulate a joint decoding order and power allocation optimization problem to maximize the sum throughput, which is solved by efficiently searching in our obtained optimal power allocation ranges. Finally, Monte Carlo simulations are conducted to confirm the accuracy of our derived exact outage probability. Numerical results show the accuracy of our deduced demarcation points of the optimal power allocation ranges. And the optimal decoding order is not constant at different total transmit power levels.

Joint subchannel power allocation for downlink NOMA systems based on quantum carnivorous plant algorithm

Currently, most existing research on non-orthogonal multiple access (NOMA) systems converts power allocation into two independent procedures, i.e., inter-subchannel power allocation and intra-subchannel power allocation. However, improper inter-subchannel power allocation will adversely affect the power allocation process of intra-subchannel. If the power allocations of inter-subchannel and intra-subchannel are optimized simultaneously, it usually needs high computational complexity, and is hard to obtain an optimal solution. To tackle this issue, this paper studies the joint subchannel power allocation for NOMA systems and proposes a new intelligent algorithm called quantum carnivorous plant algorithm (QCPA) for simultaneously optimizing inter-subchannel and intra-subchannel power allocations. Analysis of the convergence of QCPA verified its superior performance on the test functions. By utilizing the optimal solution obtained by QCPA as the power allocation scheme, energy efficiency and sum transmission rate in NOMA systems are significantly increased compared to existing traditional power allocation methods. The results above demonstrate that QCPA effectively addresses test functions and the power allocation problem for NOMA. QCPA possesses favorable convergence in comparison to other comparison algorithms and methods.

Dynamic resource allocation for energy-efficient downlink NOMA systems in 5G networks

Non-Orthogonal Multiple Access (NOMA) is a promising energy-efficient technology designed to satisfy the demands of future networks by efficiently sharing radio resources. In NOMA, the same radio resource is simultaneously assigned to two users at different power levels based on the NOMA-power domain. Resource allocation in NOMA presents a non-convex challenge, characterized as a non-deterministic polynomial (NP-hard) problem. This involves user and channel assignment and power allocation, making it an extraordinarily complex task to achieve an optimal solution. In this work, Simulated Annealing (SA) is proposed as an optimization technique for resource allocation in an energy-efficient downlink NOMA system. This resource allocation scheme addresses user and channel assignment, as well as power allocation, using SA as an efficient standalone approach to maximize energy efficiency in NOMA. SA is utilized to execute the assignment of users to channels, distribute the necessary power for each channel, and determine the power ratio among users sharing the same channel. The results obtained demonstrate a significant improvement in energy efficiency, outperforming the existing numerical methods by 22 %. The proposed SA scheme not only achieves a close optimal solution but also in less computational time, offering sufficient reliability in terms of energy efficiency enhancement when compared to the existing numerical method.

Subcarrier-users nomination process for downlink NOMA system

The non-orthogonal multiple access (NOMA) characteristics of 5G radio access allow for more efficient resource distribution. NOMA improves spectral efficiency by allowing Power domain users to transmit power concurrently with other users of time and spectrum resources. The selection of the subcarrier and the nomination of users to the subcarrier is of the utmost importance to maximize spectral efficiency fairness among the users and improve the data rate of weak users in the downlink NOMA system. The least gain subcarrier First-threshold-based Adaptive user grouping algorithm (LGSF-TBAUGA) has been devised for this purpose. This algorithm maintains a significant channel gain differential based on a threshold, thus avoiding successive interference cancellation (SIC) process imperfections. The computational complexity of the proposed technique is calculated and compared to other approaches. The power coefficients of the selected users are used to allocate power to them. The proposed method improves the weak user data and overall system sum rates. As a result, the spectrum efficiency and user fairness index have been greatly enhanced compared to some existing algorithms.

On the Performance of Noma Systems with Different User Grouping Strategies

This paper investigates several critical issues on the ergodic sum capacity and system outage performance of downlink non-orthogonal multiple access (NOMA) systems with different numbers of users per cluster sharing the same resource. The outcomes from this work suggest that NOMA systems with more users per cluster perform better under a low channel gain, while those with fewer users per cluster perform better under a high channel gain. It discloses a fact that a traditional NOMA system with a fixed user grouping scheme may not be a good choice to deal with complex channel conditions with diverse applications. To address the issue, this paper introduces a concept of mixed user grouping NOMA, which outperforms OMA and traditional NOMA significantly. The work in this paper lays a foundation for more further investigations on mixed user grouping NOMA systems.

Secure User Pairing and Power Allocation for Downlink Non-Orthogonal Multiple Access against External Eavesdropping.

We propose a secure user pairing (UP) and power allocation (PA) strategy for a downlink Non-Orthogonal Multiple Access (NOMA) system when there exists an external eavesdropper. The secure transmission of data through the downlink is constructed to optimize both UP and PA. This optimization aims to maximize the achievable sum secrecy rate (ASSR) while adhering to a limit on the rate for each user. However, this poses a challenge as it involves a mixed integer nonlinear programming (MINLP) problem, which cannot be efficiently solved through direct search methods due to its complexity. To handle this gracefully, we first divide the original problem into two smaller issues, i.e., an optimal PA problem for two paired users and an optimal UP problem. Next, we obtain the closed-form optimal solution for PA between two users and UP in a simplified NOMA system involving four users. Finally, the result is extended to a general 2K-user NOMA system. The proposed UP and PA method satisfies the minimum rate constraints with an optimal ASSR as shown theoretically and as validated by numerical simulations. According to the results, the proposed method outperforms random UP and that in a standard OMA system in terms of the ASSR and the average ASSR. It is also interesting to find that increasing the number of user pairs will bring more performance gain in terms of the average ASSR.

A streamlined user grouping in downlink NOMA systems

AbstractReducing SIC operations and interference while maintaining the same radio resources for users in a cluster is a potential research direction in non‐orthogonal multiple access (NOMA) systems. In order to reach this goal, a streamlined user grouping is proposed for a four‐user cluster in downlink NOMA systems, which is carried out based on the in‐phase and quadrature components of a constellation. In terms of bit error rate performance, the proposed scheme is superior in comparison with the conventional NOMA without user grouping and phase rotation‐based user grouping. This improvement is achieved in light of the three positive points of pulse amplitude modulation, the Gray mapping rule, and the joint maximum‐likelihood detector.

Optimal User Pairing Strategy for Minimum Power Utilization in Downlink Non-Orthogonal Multiple Access Systems

Optimal User Pairing Strategy for Minimum Power Utilization in Downlink Non-Orthogonal Multiple Access Systems

Deep Learning Aided Beamforming for Downlink Non-Orthogonal Multiple Access Systems

Deep Learning Aided Beamforming for Downlink Non-Orthogonal Multiple Access Systems

Impact of Power Consumption Models on the Energy Efficiency of Downlink NOMA Systems

While non-orthogonal multiple access (NOMA) improves spectral efficiency, it adds complexity to the receivers due to successive interference cancellation (SIC). Prior studies on the energy efficiency of NOMA overlook the SIC overhead and rely on simplistic power consumption models (PCM). To fill this gap, we first introduce PCM-κ that accounts for SIC-related power expenditure. Then, to investigate the energy efficiency of NOMA and joint transmission (JT)-coordinated multipoint (CoMP) NOMA, we formulate a power allocation problem for maximizing the energy efficiency and propose a global approach running at a centralized entity and a local algorithm running at a base station. We evaluate the energy efficiency using PCM-κ and two PCMs commonly used in the literature. Numerical analysis suggests that using simplistic PCMs leads to a few orders of magnitude overestimation of energy efficiency, especially when the receivers have low rate requirements. Despite the superiority of JT-CoMP NOMA over conventional NOMA in finding a feasible power allocation, the difference in their energy efficiency is only marginal when users have identical rate requirements and more significant in more heterogeneous settings with users having different rate requirements. Moreover, when conventional NOMA is feasible, the optimal solution for JT-CoMP NOMA converges to conventional NOMA.

Cooperative Relaying in a Three User Downlink NOMA System Using Dynamic Power Allocation

Non-orthogonal multiple access (NOMA) represents the latest addition to the array of multiple access techniques, enabling simultaneous servicing of multiple users within a singular resource block in terms of time, frequency, and code. A typical NOMA configuration comprises a base station along with proximate and distant users. The proximity users experience more favorable channel conditions in contrast to distant users, resulting in a compromised performance for the latter due to the less favorable channel conditions. When cooperative communication is integrated with NOMA, the overall system performance, including spectral efficiency and capacity, is further elevated. This study introduces a cooperative NOMA setup in the downlink, involving three users, and employs dynamic power allocation (DPA). Within this framework, User 2 acts as a relay, functioning under the decode-and-forward protocol, forwarding signals to both User 1 and User 3. This arrangement aims to bolster the performance of the user positioned farthest from the base station, who is adversely affected by weaker channel conditions. Theoretical and simulation outcomes reveal enhancements within the system’s performance.

Nonlinear symbolic regression for bit error rate prediction of NOMA systems in 5G cellular communications

Machine learning (ML) has been suggested as a promising tool in the design of telecommunication systems to overcome the challenges of traditional methods and meet the requirements regarding future cellular networks. As an enabler of 5G communications, Non-orthogonal multiple access (NOMA) has emerged to adaptively manage the existing resources and received huge attention in terms of performance analysis to confirm its efficiency in resource management. This work addresses the applications of nonlinear symbolic regression (NLSR) techniques to evolve mapping models for bit error rate (BER) prediction in the downlink NOMA systems with perfect and imperfect successive interference cancellation (SIC) receivers. In this regard, a multi-stage structure is proposed to evaluate the BER using the related inputs as well as the output of the previous stages for imperfect SIC signal decoding. Each step consists of an NLSR block with different inputs and an output, which inputs include the effective parameters and the output of the previous stages. Experimental results confirm that the NLSR techniques are able to establish modeling expressions with good prediction accuracy compared to other benchmark methods. In particular, these ML-based techniques overcome the limitation of the classical approaches in modeling a closed-form BER formula, especially for the NOMA systems with more than two users. In addition, this BER prediction tool can be utilized by the NOMA base station as new side information for more optimal resource management.

Multi-User Downlink NOMA Systems Aided by Ambient Backscattering: Achievable Rate Regions and Energy-Efficiency Maximization

In this paper, we investigate the energy efficiency of a multi-user downlink non-orthogonal multiple access (NOMA) system aided by an ambient backscatter device that modulates its own information by reflecting the incident signal coming from the NOMA transmitter. Because of the multiplicative operation at the ambient backscatter device when reflecting the transmitter’s signal, the achievable sum rate of the system is not known. Hence, we first derive the information-theoretic achievable rate region for a discrete memoryless channel and, subsequently, for Gaussian channels. We then propose a joint optimization framework for maximizing the system energy efficiency as the tradeoff and ratio between the overall sum rate and the power consumption, under user minimum rate constraints. For this, we propose a modification that simplifies the resulting non-convex optimization problems, which enables us to obtain the optimal reflection coefficient and power allocation policy analytically (up to a one line search). Numerical results demonstrate the negligible impact of the introduced modification on the optimality of our solution. Remarkably, our results show that the ambient backscatter-aided NOMA significantly outperforms OMA: the relative gain increases with the number of receivers, reaching up to 14× improvement over OMA. At last, we show the pertinence of our solution also under imperfect channel state information.

Performance Analysis of Selective DF Cooperative NOMA in Presence of Practical Impairments

In this article, we investigate a selective decode-and-forward (DF)-aided cooperative nonorthogonal multiple access (NOMA) system performance in the presence of practical impairments using imperfect successive interference cancellation (SIC) and channel estimation error (CEE). The base station communicates directly and via a relay with the two NOMA users in two-time phases. In particular, the selective DF with synchronized direct and relay transmission relaying protocol is proposed for the considered downlink NOMA system to offer enhanced quality of service and improved data reliability compared with the conventional NOMA and DF NOMA systems. The closed-form of exact and asymptotic expressions of the average bit error rate (ABER) at both NOMA users are derived considering the impact of imperfect SIC and CEE. Furthermore, the outage probability is also obtained. Finally, the improvement in the system performance acquired by the proposed scheme over the existing methods is corroborated by Monte Carlo simulations.

Outage Performance Analysis of Improper Gaussian Signaling for Two-User Downlink NOMA Systems with Imperfect Successive Interference Cancellation.

The improper Gaussian signaling (IGS) technique can improve the achievable rate of an interference-limited network by fully exploiting the second-order statistics of complex signaling. This paper addresses the outage performance analysis of a two-user downlink non-orthogonal multiple access (NOMA) system using the IGS technique in the presence of imperfect successive interference cancellation (SIC). The strong channel user (SU) adopts the IGS, while the weak channel user (WU) adopts the traditional proper Gaussian signaling (PGS). Considering a practical scenario where the transmitter has obtained the statistics of the channel coefficients instead of the instantaneous channel state information (CSI), the expressions of the achievable rates of both users under residual interference due to imperfect SIC are derived, together with their outage probabilities, subject to predetermined target rates and channel statistics. Given a fixed transmit power of the WU, both the transmit power and the degree of impropriety of the SU are optimized to minimize the outage probability subject to the outage constraint of the WU. Numerical results are provided to assess the benefits of the proposed IGS-based downlink NOMA system, which are consistent with the analysis.

Downlink Power Allocation for CR-NOMA-Based Femtocell D2D Using Greedy Asynchronous Distributed Interference Avoidance Algorithm

This paper focuses on downlink power allocation for a cognitive radio-based non-orthogonal multiple access (CR-NOMA) system in a femtocell environment involving device-to-device (D2D) communication. The proposed power allocation scheme employs the greedy asynchronous distributed interference avoidance (GADIA) algorithm. This research aims to optimize the power allocation in the downlink transmission, considering the unique characteristics of the CR-NOMA-based femtocell D2D system. The GADIA algorithm is utilized to mitigate interference and effectively optimize power allocation across the network. This research uses a fairness index to present a novel fairness-constrained power allocation algorithm for a downlink non-orthogonal multiple access (NOMA) system. Through extensive simulations, the maximum rate under fairness (MRF) algorithm is shown to optimize system performance while maintaining fairness among users effectively. The fairness index is demonstrated to be adaptable to various user counts, offering a specified range with excellent responsiveness. The implementation of the GADIA algorithm exhibits promising results for sub-optimal frequency band distribution within the network. Mathematical models evaluated in MATLAB further confirm the superiority of CR-NOMA over optimum power allocation NOMA (OPA) and fixed power allocation NOMA (FPA) techniques.

Impartial Cooperation in SWIPT-Assisted NOMA Systems With Random User Distribution

Impartial cooperation is considered in simultaneous wireless information and power transfer (SWIPT)-assisted downlink non-orthogonal multiple access (NOMA) systems with random user distribution. Unlike conventional SWIPT-assisted cooperative NOMA transmissions, we consider random user locations and investigate a transmission model in which both the near and far users of a NOMA system can serve as energy harvesting relays and forward information to each other. To assess the impact of user placement on the system performance, three user pairing schemes are designed. Closed-form expressions for the outage probability, diversity order, diversity-multiplexing trade-off (DMT), and system throughput are derived under different user location distributions, revealing that the novel SWIPT-assisted impartial cooperative NOMA improves these metrics of the near user, and does not degrade those of the far user, compared with the conventional schemes. Numerical results validate our analysis and confirm that our approach is more efficient in resource utilization, as compared to existing schemes.

User Pairing and Power Allocation in Untrusted Multiuser NOMA for Internet of Things

In the Internet-of-Things (IoT), massive sensitive and confidential information is transmitted wirelessly, making security a serious concern. This is particularly true when technologies, such as non-orthogonal multiple access (NOMA), are used, making it possible for users to access each other’s data. This paper studies secure communications in multiuser NOMA downlink systems, where each user is potentially an eavesdropper. Resource allocation is formulated to achieve the maximum sum secrecy rate, meanwhile satisfying the users’ data requirements and power constraint. We solve this non-trivial, mixed-integer non-linear programming problem by decomposing it into power allocation with a closed-form solution, and user pairing obtained effectively using linear programming relaxation and barrier algorithm. These subproblems are solved iteratively until convergence, with the convergence rate rigorously analyzed. Simulations demonstrate that our approach outperforms its existing alternatives significantly in the sum secrecy rate and computational complexity.

A deep convolutional-LSTM neural network for signal detection of downlink NOMA system

Non-orthogonal multiple access (NOMA) techniques have drawn much attention for massive connectivity, heterogeneous data traffic with ultra-low latency requirements, and ultra-high bandwidth efficiency for the future generation of wireless communication systems. This paper suggests a deep convolutional-long short-term memory (ConvNet-LSTM) aided receiver for detecting signals in the downlink NOMA system. The proposed technique implicitly estimates channel state information and recovers the transmitted symbol directly. The Bayesian approach optimizes the hyperparameters for the deep ConvNet-LSTM. The proposed learning approach is significantly more efficient than the conventional signal detection method, successive interference cancellation (SIC)-based minimum mean square error (MMSE) technique, other deep learning (DL)-based approaches, long short-term memory (LSTM), and convolutional neural networks (CNNs). It simultaneously explores the characteristics of both spatial and temporal features of the received signal for increasing the detection probability of the system. The simulations discuss the advantages of the deep ConvNet-LSTM-based receiver design for downlink NOMA communication systems in terms of bit error rate (BER), achievable rate, and mean squared error (MSE). Furthermore, the robustness of the proposed deep ConvNet-LSTM approach is evaluated for its superiority to other techniques.