Non-orthogonal Multiple Access Heterogeneous Networks Research Articles

Enhancing security offloading performance in NOMA heterogeneous MEC networks using access point selection and meta-heuristic algorithm

The research delves into the intricate domain of security offloading within the context of non-orthogonal multiple access (NOMA) heterogeneous mobile edge computing (het-MEC) networks operating over Rayleigh fading channels. The investigation centers on a system model comprising a single antenna-equipped edge user, denoted as U, which strategically offloads computational tasks to two distinct heterogeneous wireless access points (APs): the far AP (AP1) and the near one (AP2), employing NOMA techniques. Notably, the research accounts for a passive eavesdropper (E) intending to intercept the U−AP2 transmission. A four-phase protocol is proposed to ensure the security offloading process, namely SAPS, which leverages wireless access point selection (APS) and physical layer security (PLS) techniques. The focus extends to derive a closed-form expression for a novel critical system performance metric: the secrecy successful computation probability (SSCP). Furthermore, an algorithm based on Ant Colony Optimization (ACO) within the continuous domain is introduced, which aims to enhance the SSCP by intelligently determining system parameters. The impact of critical factors such as transmit power, power allocation coefficient, bandwidth, CPU frequency, and task division ratio under the SAPS scheme is explored and compared to the conventional approach using pure NOMA. Remarkably, the algorithm in the proposed scheme demonstrates up to a 3% performance improvement. The validity and accuracy of the study findings are verified through Monte-Carlo simulations. The work contributes significantly to advancing secure offloading strategies in NOMA-based MEC networks, offering valuable insights for practical deployment and optimization.

Energy-Efficient Resource Allocation for NOMA HetNets in Millimeter Wave Communications

The integration of millimeter-wave (mmWave) and non-orthogonal multiple access (NOMA) has attracted academic and industrial interest as a promising enabling approach due to their massive bandwidth support and greater spectral efficiency. In this paper, we consider NOMA heterogeneous network (HetNet) in mmWave communications, consisting of the macro-cell and small cell tiers connected through the wireless backhaul. Following this, we propose a user grouping algorithm to significantly simplify the user clustering process where each cluster consists of highly correlated users to suppress the inter-cluster interference. We then propose a hybrid analog/digital precoding scheme at the macro base station. The goal is to maximize the system’s total energy-efficiency (EE) in NOMA HetNet by jointly optimizing the transmission of hybrid precoding, power allocation, and bandwidth partition. Next, we formulate an optimization problem within the proposed framework under the minimum data rate and total maximum transmission power constraints. Due to the non-convexity nature of the formulated problem, it is challenging to obtain the optimal solution. As a result, we transform the original problem into a quasi-convex equivalent by analyzing its structure. Then we propose energy-efficient distributed power allocation algorithms to optimize the resource allocation of macro-cell and small cells. Finally, we exhibit the simulation results to demonstrate the proposed algorithm’s performance gains. The simulation results reveal that the proposed algorithmic approach surpasses state-of-the-art and traditional mmWave orthogonal multiple access systems in both capacity and EE.

Energy-efficient resource allocation for NOMA heterogeneous networks using feedback water cycle algorithm

In recent years, nonorthogonal multiple access (NOMA) has grasped the attention of all researchers in both industrial and academic fields because it has been regarded as an effective solution for 5G technologies to maximize spectral efficiency and connectivity of the system. Also, it has sufficient potential to maximize the performance of a network. Besides, the deployment of NOMA in heterogeneous networks (HetNets) satisfies the requirements of user’s explosive data traffic. However, the increasing demand for energy consumption of the wireless network provokes the researchers to establish an energy-efficient resource allocation scheme. The applications of NOMA provide better utilization of spectrum efficiency and minimize the cost of resource allocation. The resource allocation problem in wireless networks still remains a challenging task as the HetNets are suffered from mutual cross-tier interference. Hence, this research proposes a new effective hybrid optimization-based energy-efficient resource allocation scheme for NOMA HetNets by introducing a newly proposed method called Feedback Water Cycle Algorithm (FWCA). The method evaluates the user-pairing and sub-channel issue for reducing computational complexity. In addition to this, the network is analyzed for determining the power consumption and energy model with dynamic coefficients. Moreover, the developed FWCO obtained the maximum achievable rate of 25.992[Formula: see text]Mbps/Hz, maximum energy efficiency of 77.398%, maximum sum rate of 31.748[Formula: see text]Mbps/Hz, and maximum throughput of 8.888[Formula: see text]Mbps.

Joint Subchannel and Power Allocation for Energy Efficiency Optimization in NOMA Heterogeneous Networks With Energy Harvesting

Nonorthogonal multiple access (NOMA) in heterogeneous networks (HetNets) can effectively improve data rate and spectral utilization by allowing multiple users to share the same channel. However, in trying to meet various requirements of multiuser communication, maintaining a low energy becomes a serious issue in NOMA HetNets. In this article, we study a joint subchannel and power allocation scheme in order to improve the energy efficiency of small cells with energy harvesting unit in NOMA HetNets. In the scheme, we propose a modified Gale–Shapley algorithm based on the interference hypergraph for subchannel allocation that can dynamically adjust the number of small cells on the same subchannel. Furthermore, we optimize the power allocation for small cell users by the Lagrangian dual method. Numerical simulation results are presented to demonstrate that the proposed scheme achieves superior performance compared with the existing well-known methods and traditional orthogonal frequency-division multiple access system.

Research on Interference Coordination Optimization Strategy for User Fairness in NOMA Heterogeneous Networks

In order to comprehensively improve the performance of edge users in heterogeneous cellular networks and the fairness of network users, a downlink interference coordination optimization strategy in heterogeneous cellular networks with non-orthogonal multiple access (NOMA) based on the cell range expansion (CRE) and the almost blank subframe (ABS) technology is proposed. Different from the traditional interference coordination strategy, a NOMA user pairing scheme combined with ABS technology and a dynamic NOMA power allocation scheme are designed to maximize the network fairness based on the optimized throughput of the edge users. The simulation results show that the proposed optimization strategy can balance the performance of network users more effectively to improve the throughput of edge users and network fairness than other NOMA user pairing and power allocation algorithms without the complexity being increased.

Energy efficient resource allocation for uplink hybrid power domain sparse code nonorthogonal multiple access heterogeneous networks with statistical channel estimation

AbstractModern 5G heterogeneous networks (HetNets) require hybrid multiple access technology for optimal performance. The feasibility of a hybrid power domain sparse code nonorthogonal multiple access (PD‐SCMA) that integrates both power domain nonorthogonal multiple access (PD‐NOMA) and sparse code multiple access (SCMA) for an uplink hierarchical HetNet system is demonstrated. Hybrid schemes namely: Successive Codebook Ordering Assignment (SCOA) for codebook assignment (CA), opportunistic MUE‐SUE pairing (OMSP) for user pairing (UP), and a QoS‐aware power allocation (QAPA) for power allocation (PA) are developed. The SCOA algorithm is based on channel quality ordering metric, OMSP algorithm is based on channel quality diversity and pairing interference metric while the QAPA algorithm features a QoS awareness metric. A joint energy efficiency (EE) resource allocation (JEERA) algorithm that iteratively performs CA, UP, and PA for small cell user equipment (SUE) and the macro user equipment (MUE) to limit interference, improve spectral and energy efficiency is presented. The problem is formulated as a mixed integer nonconvex system EE resource allocation optimization for the small cells under QoS constraints of minimum sum‐rate, interference temperature, maximum power, and SCMA structure for a hybrid low complexity joint SIC‐Log‐MPA receiver. A modified near‐optimal dual decomposition analytical methodology featuring Dinkelbach fractional transformations is utilized to assess the system's performance on an imperfect wireless channel. Through numerical results, the proposed schemes are shown to improve the EE of the small cells in comparison with the prevalent schemes.

Energy-Minimization Task Offloading and Resource Allocation for Mobile Edge Computing in NOMA Heterogeneous Networks

Mobile edge computing (MEC) has been regarded as a promising technology to improve the quality of service (QoS) of users by offloading their computation-intensive and delay-sensitive tasks to the wireless network edge. Furthermore, applying non-orthogonal multiple access (NOMA) technology in heterogeneous networks (HetNets) has become a trend to improve system throughput and spectrum efficiency. Exploiting these benefits, we investigate the joint task offloading and resource allocation problem for MEC in NOMA-based HetNets. To minimize the energyconsumption of all users, we jointly consider task offloading decision, local CPU frequency scheduling, power control, computation resource and subchannel resource allocation. The optimization problem is challenging due to the combinatorial nature of the offloading decision and its strong coupling with the resource allocation. We thus decouple the problem into two sub-problems of offloading decision and resource allocation, and propose an efficient approach to find the joint solution by solving these two sub-problems iteratively. Simulation results show that the proposed approach can achieve a near optimal performance, and outperform other benchmark approaches in terms of saving energy consumption of all users with an acceptable complexity.

Robust resource allocation in two-tier NOMA heterogeneous networks toward 5G

This paper proposes a framework of users association and power allocation in the two-tier heterogeneous networks with nonorthogonal multiple access (NOMA). Taking account of practical wireless communication environment, the channel uncertainties are considered and described in the form of probability constraint. In order to maximize the total energy efficiency of the system and reduce the intra-cell and inter-cell interference, the joint optimization problem is formulated with the uncertain channel gain. The probability constraint is transformed to the deterministic one based on the integral transformation. With the aid of relaxation variable and successive convex approximation method, the original integer non-convex optimization problem is divided into two solvable convex subproblems. The user association algorithm and power control algorithm are presented to determine the optimal resource allocations. The simulation results show that the proposed algorithm is effective and robust to the dynamic communication environment.

Unified User Association and Contract-Theoretic Resource Orchestration in NOMA Heterogeneous Wireless Networks

Lately, the deployment of heterogeneous wireless networks has emerged, as part of the 5G vision, to cope with the users' exaggerated service demands. In this context, the application of Non-Orthogonal Multiple Access (NOMA) technique constitutes a promising solution to facilitate a balance between spectral efficiency and system complexity. In this article, we consider the problem of joint user association and uplink power allocation, in heterogeneous 5G wireless networks, employing NOMA technology. The coupled problem is treated under an incomplete information scenario, where the Base Stations (BSs) have statistical only knowledge of the users' channel conditions. To deal with the incompleteness of Channel State Information (CSI), a Contract Theory (CT) based approach is introduced. A Reinforcement Learning (RL) based methodology, capitalizing on the provided feedback from the communication environment is initially adopted, in order to achieve the users to BS association in an iterative and distributed manner. The problem of uplink power allocation is subsequently formulated as a contract between each BS and its corresponding users. The optimal power is thus obtained as the solution of the optimization of each BS's utility function, while ensuring the optimality of the utility function of each associated user, given the unique communications characteristics and type of each user. Detailed numerical evaluation of the performance of the proposed unified user association and power allocation framework is provided, via modeling and simulation, illustrating its operation, features and benefits, under densely deployed heterogeneous environments.

Fair Energy-Efficient Resource Allocation for Downlink NOMA Heterogeneous Networks

The increasing in energy consumptions of the current wireless networks, leads towards designing energy-efficient 5G networks. The application of non-orthogonal multiple access (NOMA) in the heterogeneous networks (HetNets) improves the spectrum utilization with the cost of efficient resource allocation. Hence, this article proposes optimal user-pairing and power allocation solutions towards achieving fair energy-efficient resource allocation in downlink femtocell NOMA-HetNets. In the proposed optimization process, the considered constraints are the user's transmission rate, transmit power budget at the base station (BS), and the interference. The energy consumption of both the transmitter and the receiver are considered to simulate the real system design. The Greedy Algorithm (GA) is used to achieve a low-complex optimal solution during the user-pairing process. Simultaneously, the max-min energy efficiency optimization approach is employed to maximize the minimum energy efficiency of the femtocell users to achieve the optimal power allocation solution. The mathematical formulation of the max-min energy efficiency is a non-convex fractional programming problem and is intractable. Thus, the fractional programming theory is adopted to transform the problem into a sequence of subtractive form, followed by the Sequential Convex Programming (SCP) approach to determine the optimal solution. Simulation results show that the proposed NOMA with optimal power allocation method using SCP and GA (NOMA-SCP-GA) achieves fair energy efficiency performance with lower complexity compared to the benchmark methods. Moreover, the minimum energy efficiency of the femtocell user is 38.22% higher than NOMA with Difference of Convex programming (NOMA-DC). The NOMA-SCP-GA method can assure 5G capability demands.

Hypergraph Spectral Clustering Based Spectrum Resource Allocation for Dense NOMA-HetNet

In this letter, we propose a spectrum resource allocation algorithm in non-orthogonal multiple access heterogeneous network (NOMA-HetNet). We consider a dense two-tier HetNet consisting multiple macro base station (MBS) and multiple femto base stations (FBSs), which are very close to each other. All the MBS and FBSs are working in NOMA mode. Our hypergraph spectral clustering based method is proposed to deal with the serious cumulative interference. We aim at improving the system throughput with the prerequisite that all users' fairness in the same base station is guaranteed. We analyze the computation complexity of the algorithm. The simulation result shows that our algorithm can improve the system throughput with low computational complexity.

Joint Energy Efficient Subchannel and Power Optimization for a Downlink NOMA Heterogeneous Network

Non-orthogonal multiple access (NOMA) has been considered as a key technology in the fifth-generation mobile communication networks due to its superior spectrum efficiency. Since the heterogeneous network has been emerged to satisfy users' explosive data rate requirements and large connectivity of mobile Internet, implementing NOMA policy in heterogeneous networks (HetNets) has become an inevitable trend to enhance the 5G system throughput and spectrum efficiency. In this paper, we aim to maximize the entire system energy efficiency, including the macrocell and small cells, in a NOMA HetNet via subchannel allocation and power allocation. By considering the co-channel interference and cross-tier interference, the energy efficient resource allocation problem is formulated as a mixed integer nonconvex optimization problem. It is challenging to obtain the optimal solution; therefore, a suboptimal algorithm is proposed to alternatively optimize the macrocell and the small cells resource allocation. Specifically, convex relaxation and dual-decomposition techniques are exploited to optimize the subchannel allocation and power allocation. Moreover, optimal closed-form power allocation expressions are derived for small cell and macrocell user equipments by the Lagrangian approach. Simulations results show that the proposed algorithms can converge within ten iterations and can also attain higher system energy efficiency than the reference schemes.

Energy Efficient Power Allocation for Downlink NOMA Heterogeneous Networks With Imperfect CSI

Non-orthogonal multiple access (NOMA) is a promising emerging technology that can significantly improve the utilization of spectrum and system capacity in heterogeneous wireless networks. Power allocation plays a key role in the successful deployment of NOMA. In the most prior power allocation schemes, the perfect channel state information (CSI) is assumed to be known which is difficult to obtain in a realistic environment. In this paper, we propose a power allocation scheme to maximize energy efficiency for downlink NOMA heterogeneous networks based on imperfect CSI. The system model for imperfect CSI is built, in which the optimization problem is a probabilistic non-convex problem with the constraint of outage probability. To solve the optimization problem, the probabilistic problem is transformed to a non-probabilistic problem through relaxation. The power allocation for each small cell is achieved via bisection search algorithm based on gradient value, where the trend of energy efficiency as a function of the power of the small cell is analyzed. The sequential convex programming is adapted to transform the non-convex problem to a convex problem. The closed-form solutions of power allocation factors are derived by the Lagrangian multiplier method. The simulation results show the superiority and efficiency of the proposed scheme compared with the traditional algorithms.

Energy-Efficient Resource Allocation in NOMA Heterogeneous Networks

Non-orthogonal multiple access (NOMA) has attracted much recent attention owing to its capability for improving the system spectral efficiency in wireless communications. Deploying NOMA in heterogeneous network can satisfy users' explosive data traffic requirements, and NOMA will likely play an important role in the fifth-generation (5G) mobile communication networks. However, NOMA brings new technical challenges on resource allocation due to the mutual cross-tier interference in heterogeneous networks. In this article, to study the tradeoff between data rate performance and energy consumption in NOMA, we examine the problem of energy-efficient user scheduling and power optimization in 5G NOMA heterogeneous networks. The energy-efficient user scheduling and power allocation schemes are introduced for the downlink 5G NOMA heterogeneous network for perfect and imperfect channel state information (CSI) respectively. Simulation results show that the resource allocation schemes can significantly increase the energy efficiency of 5G NOMA heterogeneous network for both cases of perfect CSI and imperfect CSI.

Distributed Power Allocation for Nonorthogonal Multiple Access Heterogeneous Networks

In this letter, we investigate the power allocation problem in nonorthogonal multiple access (NOMA) heterogeneous networks (HetNets), where the macrocell base station (MBS) and small cell base station (SBS) compete to maximize their own throughput with minimum rate requirement of each user. The throughput of MBS and SBS is formulated based on the equivalent channel gain, and the power allocation problem is captured as a Stackelberg game. A distributed power allocation algorithm is proposed to achieve the Stackelberg equilibrium. Simulation results demonstrate the convergence of the proposed algorithm. Meanwhile, it is verified that the combination of NOMA and HetNets possesses great potential to improve the spectrum efficiency compared to the orthogonal multiple access based HetNets.

Power Allocation for Downlink NOMA Heterogeneous Networks

Non-orthogonal multiple access (NOMA) and heterogeneous network (HetNet) are two significant and promising enabling techniques to further improve overall system performance for next-generation mobile communication systems. In this paper, we develop a novel NOMA HetNet through applying NOMA technique to both macrocell and small-cell of conventional HetNet, which improves the spectral efficiency whereas results in a more complex interference environment. To tackle this complicated interference problem and maximize the overall throughput of this NOMA HetNet, meanwhile ensure the desired quality of service (QoS) of each user, we mathematically formulate a power allocation problem which proves to be an NP-hard problem. Then, to deal with this optimization problem, we propose a users scheduling scheme and an iterative distributed power control algorithm. The simulation results demonstrate that compared with the conventional orthogonal multiple access (OMA) HetNet systems and single-tier NOMA networks, the combination of OMA technique and HetNet with the proposed algorithm can greatly improve the system performance in terms of spectral efficiency and outage performance.