Description:
Method for compression for remote radio heads with centralized processor performing joint decoding
NJIT Docket # 13-044
Inventors: Osvaldo Simeone, Seok-Hwan Park
Intellectual Property & Development status: US and Europe Patent Protection is pending.
NJIT is currently seeking commercial partners for the further development and commercialization of this opportunity.
Technology Brief:
Researchers at New Jersey Institute of Technology in the Department of Electrical and Computer Engineering have proposed a novel solution to optimize the compression strategies at the remote radio heads for maximizing sum rate performance.
Cloud radio access networks provide a promising approach to solve “bandwidth crunch” problem and to minimize the cost required for initial deployment or management of access points. On the uplink of the cloud radio access network, the base stations (BSs) operate as soft relay by compressing and forwarding the received signals to a cloud decoder. In the convention solution, the central decoder first decompresses the signals compressed by the BSs, and then decodes the mobile stations’ (MSs) signals. The invention is a novel design of cloud decoder and an optimization algorithm of compression, where by the cloud decoder performs joint decompression and decoding for maximizing sum-rate performance. Further, numerical results have obtained which demonstrate the advantage of the invention compared to the conventional approach based on separate decompression and decoding.
Applications
• Cellular Services
• Cellular Infrastructure
Advantages
• Significantly increase the sum-rate performance.
Inventors Bio:
Osvaldo Simeone received the M.Sc. degree (with honors) and the Ph.D. degree in information engineering from Politecnico di Milano, Milan, Italy, in 2001 and 2005, respectively. He is a Professor at the Center for Wireless Communications and Signal Processing Research (CWCSPR), New Jersey Institute of Technology (NJIT), Newark. His research interests concern wireless communications, information theory, optimization and machine learning. Dr. Simeone is a co-recipient of the 2015 IEEE Communication Society Best Tutorial Paper Award and of the Best Paper Awards at IEEE SPAWC 2007 and IEEE WRECOM 2007. He currently serves as an Editor for IEEE Transactions on Information Theory. He is a Fellow of the IEEE.