Resource Allocation Based on User Pairing and Subcarrier Matching for Downlink Non-Orthogonal Multiple Access Networks

The traditional orthogonal multiple access (OMA) is unable to satisfy the needs of large number of smart devices. To increase the transmission rate in the limited spectrum resource, implementation of both non-orthogonal multiple access (NOMA) and successive interference cancelation (SIC) is essential. In this paper, an optimal resource allocation algorithm in NOMA is proposed to maximize the total system rate in a multi-sector multi-subcarrier relay-assisted communication network. Since the original problem is a non-convex problem with mixed integer programming which is non-deterministic polynomial-time (NP)-hard, a three-step solution is proposed to solve the primal problem. Firstly, we determine the optimal power allocation of the outer users by using the approach of monotonic discrimination, and then the optimal user pairing is determined. Secondly, the successive convex approximation (SCA) method is introduced to transform the non-convex problem involving central users into convex one, and the Lagrangian dual method is used to determine the optimal solution. Finally, the standard Hungarian algorithm is utilized to determine the optimal subcarrier matching. The simulation results show that resource allocation algorithm is able to meet the user performance requirements with NOMA, and the total system rate is improved compared to the existing algorithms.

[1]  G. Ragsdell Systems , 2002, Economics of Visual Art.

[2]  Xi Zhang,et al.  Resource Allocation for Wireless Power Transmission Over Full-Duplex OFDMA/NOMA Mobile Wireless Networks , 2019, IEEE Journal on Selected Areas in Communications.

[3]  Yu Wang,et al.  An Incentive Mechanism for Privacy-Preserving Crowdsensing via Deep Reinforcement Learning , 2021, IEEE Internet of Things Journal.

[4]  Yu Wang,et al.  Efficient QoS Support for Robust Resource Allocation in Blockchain-Based Femtocell Networks , 2020, IEEE Transactions on Industrial Informatics.

[5]  Daniel K. C. So,et al.  User-Pairing Based Non-Orthogonal Multiple Access (NOMA) System , 2016, 2016 IEEE 83rd Vehicular Technology Conference (VTC Spring).

[6]  H. Vincent Poor,et al.  Application of Non-Orthogonal Multiple Access in LTE and 5G Networks , 2015, IEEE Communications Magazine.

[7]  Yao-Jen Liang,et al.  Dynamic resource allocation in mobile heterogeneous cellular networks , 2019, Wirel. Networks.

[8]  Yu Chen,et al.  A Novel Spectrum Sharing Scheme Assisted by Secondary NOMA Relay , 2018, IEEE Wireless Communications Letters.

[9]  Zhengang Pan,et al.  On the Ergodic Capacity of MIMO NOMA Systems , 2015, IEEE Wireless Communications Letters.

[10]  Yuan Wu,et al.  Optimal Power Allocation and Scheduling for Non-Orthogonal Multiple Access Relay-Assisted Networks , 2018, IEEE Transactions on Mobile Computing.

[11]  Nan Yang,et al.  Non-Orthogonal Multiple Access: Achieving Sustainable Future Radio Access , 2019, IEEE Communications Magazine.

[12]  LiYonghui,et al.  Sub-Channel and Power Allocation for Non-Orthogonal Multiple Access Relay Networks With Amplify-and-Forward Protocol , 2017 .

[13]  Tao Jiang,et al.  QoS Guaranteed Resource Allocation Scheme for Cognitive Femtocells in LTE Heterogeneous Networks with Universal Frequency Reuse , 2016, Mob. Networks Appl..

[14]  Yonghui Chen Resource Allocation for Downlink Control Channel in LTE Systems , 2011, 2011 7th International Conference on Wireless Communications, Networking and Mobile Computing.

[15]  George K. Karagiannidis,et al.  A Survey on Non-Orthogonal Multiple Access for 5G Networks: Research Challenges and Future Trends , 2017, IEEE Journal on Selected Areas in Communications.

[16]  Hao Xu,et al.  Power Control and Resource Allocation for Multi-Cell OFDM Networks With Load Coupling , 2018, IEEE Access.

[17]  Pingzhi Fan,et al.  Impact of User Pairing on 5G Nonorthogonal Multiple-Access Downlink Transmissions , 2016, IEEE Transactions on Vehicular Technology.

[18]  Derrick Wing Kwan Ng,et al.  Resource Allocation for MC-NOMA Systems with Cognitive Relaying , 2017, 2017 IEEE Globecom Workshops (GC Wkshps).

[19]  Harold W. Kuhn,et al.  The Hungarian method for the assignment problem , 1955, 50 Years of Integer Programming.

[20]  Xiaohui Zhao,et al.  Joint Resource Allocation for OFDM-Based Cognitive Two-Way Multiple AF Relays Networks With Imperfect Spectrum Sensing , 2018, IEEE Transactions on Vehicular Technology.

[21]  H. Kuhn The Hungarian method for the assignment problem , 1955 .

[22]  S. Ohno,et al.  Subcarrier Allocation for multi-user OFDM system , 2005, 2005 Asia-Pacific Conference on Communications.

[23]  I. Abdel-Qader,et al.  Cross-layer design of a dynamic resource allocation control for 3GPP2 1xEV-DV systems , 2004, 2004 IEEE Electro/Information Technology Conference.

[24]  Xinping Guan,et al.  Energy efficient resource allocation based on relay selection and subcarrier pairing with channel uncertainty in cognitive radio network , 2019, Comput. Networks.

[25]  Wei Liang,et al.  User Pairing for Downlink Non-Orthogonal Multiple Access Networks Using Matching Algorithm , 2017, IEEE Transactions on Communications.

[26]  Yu Wang,et al.  DREAM: Online Control Mechanisms for Data Aggregation Error Minimization in Privacy-Preserving Crowdsensing , 2020, IEEE Transactions on Dependable and Secure Computing.

[27]  Wanming Hao,et al.  Optimal resource allocation for cooperative orthogonal frequency division multiplexing-based cognitive radio networks with imperfect spectrum sensing , 2015, IET Commun..

[28]  Chee Yen Leow,et al.  Two-way relay assisted non-orthogonal multiple access , 2019, Comput. Commun..

[29]  Xinping Guan,et al.  Energy-Spectral Efficiency Optimization in Vehicular Communications: Joint Clustering and Pricing-Based Robust Power Control Approach , 2020, IEEE Transactions on Vehicular Technology.