Resource Allocation Of Heterogeneous Networks Based On NOMA

2020,a pandemic happened suddenly.Many changes have taken place in human lifestyles,and many offline activities have been transferred to online activities.In such a context,there is a greater need for high speed and wide connectivity networks.Traditional orthogonal multiple access techniques can no longer meet the growing communication needs,so non-orthogonal multiple access techniques have become a hot research topic nowadays.In addition,the emergence of heterogeneous technologies and D2 D communications meet the explosive data rate requirements of users and the large connectivity of the mobile Internet,so combining NOMA with them has become an inevitable trend to improve system throughput and spectral efficiency.And since spectrum sharing between multiple users and multi-layer cells leads to co-layer and cross-layer interference,effective resource allocation and interference management become research challenges for heterogeneous networks.In view of this,this paper discusses the resource allocation optimization problem from the perspective of the transmitter side based on the uplink non-orthogonal multiple access system,combined with the heterogeneous model and D2 D communication.The details of the research are as follows.(1)First,an overview analysis of domestic and international research on non-orthogonal multiple access systems is presented,where resource allocation is essential to improve system performance.Second,existing user grouping and power allocation algorithms are summarized specifically for non-orthogonal multiple access uplink and downlink systems in the power domain.(2)In order to comply with the concept of green communication,the energy efficiency optimization problem in non-orthogonal multi-access heterogeneous networks is studied.Since the energy efficiency is optimized at the expense of spectral efficiency,the scheme innovatively incorporates a partitioning scenario.It is assumed that the base station is configured with directional antennas,thus corresponding to each interval.Since it cannot be solved directly,this optimization problem is decomposed into two parts: power allocation and sub-channel selection.The power allocation is iterated by the Lagrangian subgradient method and the sub-channel allocation is done by a selection algorithm based on the greedy principle.Finally,the simulation experiments conclude that the algorithm can achieve fast convergence,the energy efficiency is highest when the number of sectors is three,and the performance of this scheme is better in terms of energy efficiency than the non-orthogonal multiple access scheme without considering partitioning.(3)In order to ensure the fairness of edge users,the sum rate optimization problem in nonorthogonal multiple access networks based on D2 D communication is studied.Because edge users are far from the central base station and have poor channel conditions,D2 D communication technology is added to enable them to communicate directly without passing through the base station.Since it cannot be solved directly,the optimization problem is decomposed into user clustering,subchannel selection,and power allocation.Among them,the user clustering algorithm has improved the traditional clustering algorithm K-means algorithm.The sub-channel matching adopts one-to-one trilateral matching,and the power distribution part uses successive approximation method iterative loop.Finally,the simulation results show that the improved K-means algorithm can obtain lower mean square error and improve user relevance.And as the number of users increases,the scheme is indeed beneficial to improve user fairness compared to the traditional orthogonal multiple access scheme and non-orthogonal multiple access scheme.