LAUSR

Required throughput for a fronthaul in a cloud-radio access network tremendously increases and becomes a bottleneck in a communication network with wide bandwidth and a large number of antennas. To reduce the fronthaul capacity requirement, more digital function blocks are shifted from a central unit to a distributed unit. In this study, we consider separated delivery of data and pilot signals with different compression rates under time-varying channels to reduce fronthaul burden. By analyzing channel prediction error based on a Kalman filter, an achievable rate for uplink data is derived. The fronthaul rates for data and pilots are derived using rate-distortion theory. Both uplink rate maximization and fronthaul rate minimization are simultaneously designed by considering the data and pilot signal distortions as well as the frame structure. First, the optimization of signal distortion with a fixed pilot interval is investigated. Next, a sub-optimal algorithm to find the pilot interval with the fixed signal distortion is developed. Finally, an iterative algorithm to obtain the sub-optimal solution, which is the joint solution of signal distortion and pilot interval, is proposed. The numerical results demonstrate that the proposed algorithm can provide convergent solutions.