Front-Haul Compression Using Scheduling Side Information for Cloud Radio Access Networks

IEEE Global Communications Conference(2015)

引用 3|浏览8
Cloud Radio Access Network (C-RAN) is a novel mobile network architecture that allows for efficient and economic building, upgrading and maintenance of RAN networks to cope with increasing mobile traffic data. The main idea behind C-RAN is to maintain distributed remote radio head (RRH) units for transmission and reception of radio signals, while pool the Baseband Units (BBUs) from multiple base stations into a centralized location for statistical multiplexing gain. The BBUs are connected to RRH via front-haul links. Although the C-RAN architecture enjoys significant advantages in terms of both the capital expenditure (CAPEX) and the operational expenditure (OPEX) over traditional networks, it also exerts considerable burden on the capacity- constrained front-haul links of transporting the high bandwidth complex baseband data between RRH and BBUs. Fortunately, the LTE signal is inherently redundant and compressible. In this paper, we propose a low-complexity, frequency domain, front-haul compression algorithm, that leverages the user scheduling side-information available at the BBU pool, in addition to the LTE signal redundancy, to achieve a compression ratio of $10$X for a full-buffer traffic model. We also provide extensive link-level and system-level simulations to validate the performance of our proposed front-haul compression algorithm on simulated LTE signal.
front-haul compression,scheduling side information,cloud radio access networks,mobile network architecture,RAN network maintenance,RAN network upgrading,mobile traffic data,C-RAN,distributed remote radio head units,distributed RRH units,radio signal transmission,radio signal reception,baseband units,BBU,statistical multiplexing gain,capital expenditure,CAPEX,operational expenditure,OPEX,capacity-constrained front-haul links,high bandwidth complex baseband data,low-complexity frequency domain front-haul compression algorithm,LTE signal redundancy,link-level simulations,system-level simulations,performance validation
AI 理解论文
Chat Paper