Compressive image broadcasting in MIMO systems with receiver antenna heterogeneity

In this work we consider image delivery in MIMO broadcast networks with diverse channel quality and varying numbers of antennas across receivers. In such systems, performance is normally constrained by the weakest users with either a low channel SNR or only a single receive antenna. To address both dimensions of heterogeneity, we propose a new analog image delivery system that adapts seamlessly along both dimensions simultaneously. Our sender scales the DWT coefficients according to a power allocation strategy, and generates linear combinations of the coefficients using compressive sensing (CS), before transmitting them with amplitude modulation. On the receiving side, the received physical layer symbols are passed directly to the source decoder without conventional MIMO decoding, and the DWT coefficients are recovered using a CS decoder. There are two main contributions of our system. First, integrating CS into MIMO transmission ensures that the reconstructed image quality at the receivers is commensurate with both the channel SNR and the MIMO channel dimension. Second, we introduce a power allocation strategy to achieve a performance tradeoff between receivers with different antenna numbers. Experimental results show that the proposed system outperforms both the analog reference SoftCast and the conventional digital system known as HM-STBC. The average gain is 2.92dB over SoftCast for single-antenna users and 1.53dB over HM-STBC for two-antenna users.