2017/01/23 by Photios A. Stavrou, Jan Østergaard, Stavrou, Photios A. +5
Computer Science · Engineering · #Distributed Sensor Networks and Detection Algorithms #Energy Harvesting in Wireless Networks #FOS: Computer and information sciences #Information Theory (cs.IT) #Wireless Communication Security Techniques
paper · pdf · doi:10.48550/arxiv.1701.06368
openalex publication_date 2017/01/23 · openalex created_date 2022/10/03 · openalex updated_date 2026/07/28
We deal with zero-delay source coding of a vector Gaussian autoregressive\n(AR) source subject to an average mean squared error (MSE) fidelity criterion.\nToward this end, we consider the nonanticipative rate distortion function\n(NRDF) which is a lower bound to the causal and zero-delay rate distortion\nfunction (RDF). We use the realization scheme with feedback proposed in [1] to\nmodel the corresponding optimal "test-channel" of the NRDF, when considering\nvector Gaussian AR(1) sources subject to an average MSE distortion. We give\nconditions on the vector Gaussian AR(1) source to ensure asymptotic\nstationarity of the realization scheme (bounded performance). Then, we encode\nthe vector innovations due to Kalman filtering via lattice quantization with\nsubtractive dither and memoryless entropy coding. This coding scheme provides a\ntight upper bound to the zero-delay Gaussian RDF. We extend this result to\nvector Gaussian AR sources of any finite order. Further, we show that for\ninfinite dimensional vector Gaussian AR sources of any finite order, the NRDF\ncoincides with the zero-delay RDF. Our theoretical framework is corroborated\nwith a simulation example.\n