H2H/M2M共存场景下基于图论的干扰协调机制

Graph Theory Based Interference Coordination for H2H/M2M Coexisting Scenarios

针对H2H/M2M共存的LTE-A全频复用异构蜂窝网络,提出基于最大独立集的干扰协调和RB扩展分配算法(CGMMIS算法),以在保证RB分配连续性的前提下优化系统和速率。首先,基于节点之间的相对干扰强度构建干扰图。然后,CGMMIS算法将存在强干扰的节点分到不同的独立集中,同时最大化独立集内各节点的信道增益之和。最后,利用RB扩展分配算法保证RB分配连续性,使得节点仅选择使其可达速率最大的独立集。仿真结果表明,在M2M设备密集部署的场景下,CGMMIS算法的系统和速率明显优于非协同算法和基于着色的最大独立集随机搜索算法。

For human-to-human(H2H)and machine-to-machine(M2M)communications coexisting scenarios in the co-channel deployed LTE-A heterogeneous networks,a maximum independent set(MIS)based interference coordination and resource block(RB)expansion allocation algorithm(CGMMIS)was proposed to maximize the system sum rate while ensuring RB allocation continuity.Firstly,the interference graph is obtained according to the relative interference between two nodes.Secondly,CGMMIS algorithm divides the nodes with strong interference to each other into different MISs and maximizes the sum channel gain of the nodes in the MIS.However,a node may belongs to multiple MISs under this circumstance.Lastly,in order to guarantee the consecutive allocation of RBs,the RB expansion allocation me-thod is exploited in CGMMIS algorithm,in which the node will only select the MIS that can maximize its achievable rate.Simulation results demonstrate that in the dense deployment scenario of M2M devices,the proposed CGMMIS algorithm is superior to both the non-cooperative algorithm and the random graph coloring based MIS search algorithm in terms of system sum rate.