Resource allocation for MU-MIMO non-orthogonal multiple access (NOMA) system with interference alignment

Non-orthogonal multiple access (NOMA) has attracted a lot of attention recently due to its superior spectral efficiency and could play a vital role in improving the capacity of future networks. This paper considers resource allocation for a downlink, multi-user (MU) MIMO-NOMA system that aims at maximizing the sum rate with interference alignment (IA) technique. Using singular decomposition value (SVD) based IA, we propose IA based NOMA system in which a number of users are grouped together while the others are aligned to the null space as interference. The targeted group of users employ NOMA with a low complexity hierarchical power allocation scheme for sum rate maximization. In addition, an optimization problem is formulated to maximize the sum rate under the total power and proportional fairness constraints. A low complexity sub-optimal solution for two-user scenario is obtained and then extended to the multi-user case by a hierarchical pairing scheme. Another approach is proposed to allocate the transmission power of each user using an iterative subgradient method. Simulation results show that the proposed schemes provide better performance than an existing scheme and perform close to the optimal one. In addition, the simulation scenario considers the case where two users share the data streams while performing IA as compared to the case where all users are sharing it without IA. Simulation results verify that applying IA with NOMA could improve the achievable sum rate and offers simplicity in terms of successive interference cancellation (SIC) application.

[1]  Vincent W. S. Wong,et al.  Throughput-Efficient Scheduling and Interference Alignment for MIMO Wireless Systems , 2014, IEEE Transactions on Wireless Communications.

[2]  Joonhyuk Kang,et al.  Design of user clustering and precoding for downlink non-orthogonal multiple access (NOMA) , 2015, MILCOM 2015 - 2015 IEEE Military Communications Conference.

[3]  Stephen P. Boyd,et al.  Subgradient Methods , 2007 .

[4]  Zhengang Pan,et al.  Energy efficiency optimization for fading MIMO non-orthogonal multiple access systems , 2015, 2015 IEEE International Conference on Communications (ICC).

[5]  H. Vincent Poor,et al.  A General MIMO Framework for NOMA Downlink and Uplink Transmission Based on Signal Alignment , 2015, IEEE Transactions on Wireless Communications.

[6]  Erik G. Larsson,et al.  Energy and Spectral Efficiency of Very Large Multiuser MIMO Systems , 2011, IEEE Transactions on Communications.

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

[8]  Fa-Long Luo,et al.  Signal processing for 5G : algorithms and implementations , 2016 .

[9]  Yang Liu,et al.  On the Capacity Comparison Between MIMO-NOMA and MIMO-OMA , 2016, IEEE Access.

[10]  Jie Tang,et al.  Energy Efficiency Optimization With Interference Alignment in Multi-Cell MIMO Interfering Broadcast Channels , 2015, IEEE Transactions on Communications.

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

[12]  Anass Benjebbour,et al.  Performance Evaluation of Non-Orthogonal Multiple Access Combined with Opportunistic Beamforming , 2014, 2014 IEEE 79th Vehicular Technology Conference (VTC Spring).

[13]  Muhammad Ali Imran,et al.  How much energy is needed to run a wireless network? , 2011, IEEE Wireless Communications.

[14]  Sen Wang,et al.  Sum rate optimization for MIMO non-orthogonal multiple access systems , 2015, 2015 IEEE Wireless Communications and Networking Conference (WCNC).

[15]  Derrick Wing Kwan Ng,et al.  Optimal Joint Power and Subcarrier Allocation for MC-NOMA Systems , 2016, 2016 IEEE Global Communications Conference (GLOBECOM).