Structured compressed sensing based narrowband interference elimination for in-home power line communications

The structured compressed sensing based framework for the estimation of NarrowBand Interference (NBI) in power line communication is proposed, which facilitates in-home interconnection and prevents the wired consumer electronics devices from contamination of NBI. To recover the NBI accurately, the Structured Compressed Sensing (SCS) theory is introduced, and the method of SCS based Temporal Differential Measuring (SCS-TDM) is proposed, which fully exploits the temporal correlation of NBI. By exploiting the repeated training sequences, the NBI measurements matrix is acquired. With the exploitation of the prior partial support information, a more effective greedy algorithm, structured prior aided sparsity adaptive matching pursuit, is proposed. The performance of the proposed algorithm is theoretically guaranteed, and simulation results validate that the proposed method significantly outperforms existing counterparts.