Multicarrier NOMA Research Articles

Novel Resource Allocation Algorithm for IoT Networks With Multicarrier NOMA

Novel Resource Allocation Algorithm for IoT Networks With Multicarrier NOMA

A novel user clustering and efficient resource allocation in non-orthogonal mutliple access for IoT networks.

Optimal resource allocation is crucial for 5G and beyond networks, especially when connecting numerous IoT devices. In this paper, user clustering and power allocation challenges in the downlink of a multi-carrier NOMA system are investigated, with sum rate as the optimization objective. The paper presents an iterative optimization process, starting with user clustering followed by power allocation of the users. Although the simultaneous transmission for multiple users achieves high system throughput in NOMA, it leads to more energy consumption, which is limited by the battery capacity of IoT devices. Enhancing energy efficiency by considering the QoS requirement is a primary challenge in NOMA-enabled IoT devices. Currently, fixed user clustering techniques are proposed without considering the diversity and heterogeneity of channels, leading to poor throughput performance. The proposed user clustering technique is based on the partial brute force search (P-BFS) method, which reduces complexity compared to the traditional exhaustive search method. After the user clustering, we performed optimal power allocation using the Lagrangian multiplier method with Karush-Kuhn-Tucker (KKT) optimal conditions for each user assigned to a subchannel in each cluster. Lastly, a deep neural network (DNN) based proposed P-BFS scheme is used to reduce resource allocation's complexity further. The simulation results show a significant improvement in the sum rate of the network.

Energy efficient multi-carrier NOMA and power controlled resource allocation for B5G/6G networks

Energy efficient multi-carrier NOMA and power controlled resource allocation for B5G/6G networks

User-Centric Resource Allocation in Downlink Multi-Carrier NOMA System With Coexistence of URLLC and eMBB Users

User-Centric Resource Allocation in Downlink Multi-Carrier NOMA System With Coexistence of URLLC and eMBB Users

Outage Analysis of Sparse Vector Coding-Based Downlink Multicarrier NOMA for URLLC

Ultra-reliable and low latency communication (uRLLC) is a promising use case in the fifth generation and beyond systems for critical and delay-sensitive applications with aid of short packet transmission. Nevertheless, multi-carrier non-orthogonal multiple access (MCNOMA) is a promising technique to achieve spectral efficiency and massive connectivity, however, inter-carrier interference (ICI) stands out to be a major downside. Recently, sparse vector coding (SVC) is proposed to fulfill the trade-off between reliability and latency, thereby achieving the benchmarks of uRLLC. In this paper, SVC based downlink MCNOMA (SVC-MCNOMA) system is considered and first it is shown that SVC-MCNOMA is free from ICI due to the sparse nature of the information. Further, compressed sensing-based recovery at the receiver end helps in reducing the latency as well as enhances reliability. Moreover, to study the system performance, this paper derives the closed form outage expressions of the SVC-MCNOMA system over the Rician fading channel and through Monte-Carlo simulation, the analytical results are validated. The analyses demonstrate that SVC-MCNOMA outperforms conventional MCNOMA (C-MCNOMA), thereby achieving spectral efficacy, ultra-reliability with low latency and eradicates the effect of ICI.

Subchannel and power optimization for sum rate maximization in downlink multicarrier NOMA networks

In a multicarrier NOMA system, the subchannel allocation (SA) and power allocation (PA) are intricately linked and essential for improving system throughput. Also, for the successful execution of successive interference cancellations (SIC) at the receiver, a minimum power gap is required among users. As a result, this research comes up with optimization of the SA and PA to maximize the sum rate of the NOMA system while sticking to the minimum power gap constraint in addition to minimum user rate, maximum number of users in a subchannel and power budget constraints for downlink transmission in multicarrier NOMA networks. To ensure that the formulated problem can be solved in polynomial time, we propose solving it in two stages; SA followed by PA. To obtain SA, we investigate four algorithms: Greedy, WSA, WCA, and WCF. For PA, we propose a low-complexity algorithm. We compare the performance of the proposed method with benchmark method that does not consider the minimum power gap constraint. We conclude that employing WCF algorithm with the PA algorithm gives the best sum rate performance.

A Low Complexity Algorithm of Dynamic Resource Allocation for Downlink Multi-Carrier NOMA Systems

This paper investigates the sub-channels and power allocation issue in the multi-carrier NOMA communication system. To maximize the sum rate of the system, we design a fast dynamic resource allocation (FDRA) algorithm. The algorithm can quickly identify the interference nodes with poor channel conditions, and reduces the search complexity of the algorithm. By jointly optimizing sub-carrier and power resource allocation, the proposed scheme can take full advantage of the channel capacity, and maximize the system performance while ensuring the quality of service (QoS) of each user. Simulation results show that when compared with the joint resource allocation (JRA) algorithm and the genetic algorithm (GA), the FDRA algorithm can achieve the best performance on the complexity and the sum rate of the system. Thus, the proposed algorithm can provide a fast and efficient resource allocation scheme for the downlink multi-carrier NOMA systems.

Optimal Resource Allocation for Multicarrier NOMA in Short Packet Communications

Wireless communication system needs a spectrum efficient, a power efficient and a cost efficient communication with high throughput to provide communication for ubiquities applications such as voice, data, picture, video, movies, multimedia services, Global Positional System (GPS), navigational system, telemedicine and other value added communication. Non-Orthogonal Frequency Division Multiplexing (NOMA) has become a popular technique for transmission of signals over wireless channels. In the first phase, MIMO system which uses NOMA is used. User signals are divided into parallel streams, using NOMA and are transmitted by the antenna array which propagates through the fading channel. signals are weighted using the Minimum Variance Distortionless Response (MVDR) where the weights are such that the output signal has minimum variance and the desired signal is not distorted. The parallel weighting scheme for interference cancellation leads to a faster, reliable and higher capacity system and results in parallel interference cancellation. Iterative process is also presented in this work, where the approximate weights are found out based on the minimum error value. Both the MVDR weighting and the approximate weighting are evaluated with the help of Bit Error Rate (BER) curves. The curves are plotted for both the Rayleigh and Rician channels. Various plots are obtained by varying the number of antennas in the array and also by varying the length of the user signal. All the BER curves achieved good results and from the analysis it is found that system performs better when Rayleigh channel was considered.

Energy-efficient resource allocation optimization algorithm in industrial IoTs scenarios based on energy harvesting

Due to the rapid development of the mobile Internet and the Internet of Things (IoTs), the requirements of users and enterprises for data transmission have increased exponentially. Non-orthogonal multiple access technology can improve the spectrum efficiency of the system, but it also brings huge energy consumption. This paper studies the resource allocation of non-orthogonal multiple access systems from the perspective of energy efficiency. For the multi-carrier downlink NOMA communication scenario, the circuit energy consumption model related to the transmission rate is considered. Based on the GPE energy efficiency criterion that helps reduce the complexity of channel estimation, the joint optimization algorithm of channel resources and power resources is studied. By establishing a bilateral matching model between users and sub-channels, a low-complexity channel resource allocation algorithm based on centralized scheduling is proposed. In order to avoid the phenomenon that the data transmission quality is seriously degraded due to the energy saving of the system, the limitation of user service quality requirements is also added to the established optimization problem. The algorithm performance simulation experiment shows that the algorithm in this paper has higher average energy efficiency of the system compared with the non-cooperative centralized scheduling and the distributed RB allocation algorithm.

Performance evaluation of a power allocation algorithm based on dynamic blocklength estimation for URLLC in the multicarrier downlink NOMA systems

Performance evaluation of a power allocation algorithm based on dynamic blocklength estimation for URLLC in the multicarrier downlink NOMA systems

Throughput maximization for underlay CR multicarrier NOMA network with cooperative communication

Throughput maximization for underlay CR multicarrier NOMA network with cooperative communication

Energy Efficiency Maximization in Downlink Multi-Cell Multi-Carrier NOMA Networks With Hardware Impairments

In this paper, we investigate energy efficiency (EE) maximization in multicell multicarrier non-orthogonal multiple access (MCMC-NOMA) networks with hardware impairments (HIs). We formulate the optimization problem as a mixed integer nonlinear NP-hard problem, which is difficult to solve efficiently. To solve this problem, we decompose it into two subproblems. The first subproblem is the user and base station (BS) association and subchannel assignment problem, where binary whale optimization algorithm (BWOA) is proposed to handle it. For the second subproblem of the non-convex power allocation problem, successive pseudo-convex approximation (SPCA) is employed to establish the problem’s pseudo-convexity. The approximate problem is separable into a sequence of equivalent problems that can be easier to solve. Each problem of the obtained sequence has a stationary point solution and is guaranteed to converge. The simulation results demonstrate that the proposed algorithm achieves a performance comparable to that of the successive lower bound maximization (SLBM) algorithm and outperforms both fractional transmit power allocation (FTPA) benchmark for NOMA and the conventional orthogonal multiple access (OMA).

Optimal Resource Allocation for Multicarrier NOMA in Short Packet Communications

In this paper, we study the resource allocation problem for downlink multicarrier non-orthogonal multiple access systems with short-packet communications (MC-NOMA-SPC). In contrast to long-packet communications in conventional wireless systems, SPC suffers from a transmission rate degradation and an unavoidable decoding error rate. Thus conventional resource allocation based on the Shannon capacity assuming infinite blocklength is no longer optimal. In this paper, we propose to use the effective-throughput as the performance metric to evaluate the tradeoff between the transmission rate and the decoding error rate. Building on that, we jointly optimize the subcarrier assignment, transmission power allocation, and transmission rate adaptation of each user to maximize the total weighted effective-throughput subject to transmission reliability and various practical constraints. Since the formulated problem belongs to a non-convex mixed integer nonlinear programming (MINLP) problem, we develop an efficient algorithm based on the dynamic programming (DP) recursion framework to obtain its optimal solutions. We further propose a low-complexity algorithm based on the principles of block coordinate descent (BCD) and concave-convex procedure (CCCP). Finally, the simulation results show that the proposed low-complexity algorithm can achieve similar performance as that of the optimal solution and outperform the other baseline schemes significantly.

Clustering and Auction-Based Power Allocation Algorithm for Energy Efficiency Maximization in Multi-Cell Multi-Carrier NOMA Networks

In this paper, we investigate the energy efficiency (EE) maximization in multi-cell multi-carrier non-orthogonal multiple access (MCMC-NOMA) networks. To achieve this goal, an optimization problem is formulated then the solution is divided into two parts. First, we investigate the inter-cell interference mitigation and then we propose an auction-based non-cooperative game for power allocation for base stations. Finally, to guarantee the rate requirements for users, power is allocated fairly to users. The simulation results show that the proposed scheme has the best performance compared with the existing NOMA-based fractional transmit power allocation (FTPA) and the conventional orthogonal frequency division multiple access (OFDMA).

Trigonometric transforms and precoding strategies for OFDM‐based uplink hybrid multi‐carrier nonorthogonal multiple access

AbstractAn uplink hybrid nonorthogonal multiple access (h‐NOMA) scheme utilizing power domain multiplexing is adopted in this paper for orthogonal frequency–division multiplexing (OFDM)–based systems. The OFDM‐based NOMA systems can achieve high spectral efficiency with resilience to wireless multipath fading. The h‐NOMA maintains a low interference level per resource block or low complexity of multiuser detection (MUD) implementation at the receiver and also achieves consistent fairness performance by restricting the maximum number of users per resource block. An improved user clustering algorithm for OFDM‐based h‐NOMA system under the assumption of user's distinct data rate requirement is presented here. The proposed algorithm takes into consideration both the channel gain of all activated users and the different data rate requirements of weak channel gain users. High peak‐to‐average power ratio (PAPR) and performance degradation due to strict frequency synchronization requirements are the main drawbacks of such an OFDM‐based uplink h‐NOMA system. High PAPR of multicarrier NOMA is addressed here with precoding techniques. An enhanced minimum mean square error (MMSE) receiver performing joint equalization and carrier frequency offset (CFO) compensation using low‐complexity banded‐matrix implementation is proposed to cancel interference in the frequency domain. The MUD is implemented with low‐complexity successive interference cancellation (SIC) using bandedmatrix approximation of the interference matrix in the presence of CFO. Moreover, the possibility of utilizing efficient trigonometric transforms to implement OFDM‐based NOMA is studied with CFO and estimation errors. For OFDM‐based h‐NOMA system, an efficient combination of different trigonometric transform configurations to constitute the multicarrier basis for OFDM with a suitable precoding strategy for PAPR reduction is studied.

Joint subcarrier assignment and weighted-sum energy-efficient power allocation in multi-carrier uplink NOMA relay networks

In this paper, the problem of joint subcarrier assignment and weighted-sum energy-efficient power allocation (J-SA-WSEE-PA) in multi-carrier uplink NOMA relay networks is considered. Specifically, the aim is to assign subcarriers to network users, while maximizing the weighted-sum energy-efficiency, subject to quality-of-service (QoS) constraints. The J-SA-WSEE-PA problem is shown to be non-convex, and thus is computationally-expensive. In turn, it is split into two sub-problems: (1) WSEE maximizing power allocation per subcarrier, and (2) matching-theoretic subcarrier assignment. For the first sub-problem, a low-complexity iterative solution procedure is devised to optimally solve the WSEE-maximizing power allocation problem per subcarrier. As for the second sub-problem, two linear time-complexity stable matching algorithms based on the hospitals–residents matching problem are proposed to assign subcarriers to network users. Simulation results are presented to validate the devised solution procedure and the proposed stable matching algorithms, where it has been shown that they yield comparable network sum energy-efficiency to the J-SA-WSEE-PA scheme, while satisfying QoS constraints, and with lower computational complexity.

A Deep Learning-Based Approach to Power Minimization in Multi-Carrier NOMA With SWIPT

Simultaneous wireless information and power transfer (SWIPT) and multi-carrier non-orthogonal multiple access (MC-NOMA) are promising technologies for future fifth generation and beyond wireless networks due to their potential capabilities in energy-efficient and spectrum-efficient system designs, respectively. In this paper, the joint downlink resource allocation problem for a SWIPT-enabled MC-NOMA system with time switching-based receivers is investigated, where pattern division multiple access (PDMA) technique is employed. We focus on minimizing the total transmit power of the system while satisfying the quality-of-service requirements of each user in terms of data rate and harvested power. The corresponding optimization problem is a non-convex and a mixed integer programming problem which is difficult to solve. Different from the conventional iterative searching-based algorithms, we propose an efficient deep learning-based approach to determine an approximated optimal solution. Specifically, we employ a typical class of deep learning model, namely, deep belief network (DBN), where the detailed procedure of the developed approach consists of three parts, i.e., data preparation, training, and running. The simulation results demonstrate that the proposed DBN-based approach can achieve similar performance of power consumption to the exhaustive search method. Furthermore, the results also confirm that MC-NOMA with PDMA outperforms MC-NOMA with sparse code multiple access, single-carrier non-orthogonal multiple access, and orthogonal frequency division multiple access in terms of power consumption in SWIPT-enabled systems.

Subcarrier and Power Allocation for the Downlink of Multicarrier NOMA Systems

This paper investigates the joint subcarrier and power allocation problem for the downlink of a multi-carrier non-orthogonal multiple access (MC-NOMA) system. A novel three-step resource allocation framework is designed to deal with the sum rate maximization problem. In Step 1, we relax the problem by assuming that each of the users can use all the subcarriers simultaneously. With this assumption, we prove the convexity of the resultant power control problem and solve it via convex programming tools to get a power vector for each user. In Step 2, we allocate the subcarriers to users by a heuristic greedy manner with the obtained power vectors in Step 1. In Step 3, the proposed power control schemes used in Step 1 are applied once more to further improve the system performance with the obtained subcarrier assignment of Step 2. To solve the maximization problem with fixed subcarrier assignments in both Step 1 and Step 3, a centralized power allocation method based on projected gradient descent algorithm and two distributed power control strategies based, respectively, on pseudo-gradient algorithm and iterative waterfilling algorithm are investigated. Numerical results show that our proposed three-step resource allocation algorithm could achieve comparable sum rate performance to the existing near-optimal solution with much lower computational complexity and outperforms power controlled OMA scheme. Besides, a tradeoff between user fairness and sum rate performance can be achieved via applying different user power constraint strategies in the proposed algorithm.