Structured Compressive Sensing for Channel Estimation in OFDM System with ESPAR Antenna

Electrical steerable passive array radiator (ESPAR) antenna is promising a low-power multi-antenna system which has a comparable performance to the multiple-input multiple-output (MIMO) system. However, the main drawback of the ESPAR antenna adaptation into the current generation of orthogonal frequency division and multiplexing (OFDM) systems is its channel estimation. In the ESPAR-OFDM system, channel estimation is required for each antenna element received signal. Moreover, the input for the channel estimation process is the pilot tones combination from all antenna elements. Compressive sensing (CS) based channel estimation has been proposed as a solution for the ESPAR-OFDM channel estimation. However, the CS method still suffers from huge matrix multiplication complexity. This paper proposes a structured CS method which can overcome the matrix multiplication problem in the CS based channel estimation for the ESPAR-OFDM system.