Optimal compression and storage strategies for fronthaul transfer and HARQ buffering

Abstract

The Cloud-Radio Access Network (C-RAN) cellular architecture relies on the transfer of complex baseband signals to and from a central unit (CU) over digital fronthaul links to enable the virtualization of the baseband processing functionalities of distributed radio units (RUs). Key challenges in the implementation of C-RAN are the capacity bottleneck and latency that result from the transfer of information between RU and CU on the connecting fronthaul link. In this dissertation, I rst aim at the design of a practical symbol-by-symbol fronthaul quantization algorithm that implements the theoretical idea of multivariate compression for the C-RAN downlink. As compared to current standards, the proposed multivariate quantization (MQ) only requires changes in the CU processing while no modication is needed at the RUs. The algorithm is extended to enable the joint optimization of downlink precoding and quantization, reduced-complexity MQ via successive block quantization, and variable-length compression. Numerical results, which include performance evaluations over standard cellular models, demonstrate the advantages of MQ and the merits of a joint optimization with precoding. On the other hand, a key practical constraint on the design of Hybrid Automatic Repeat Request (HARQ) schemes is the size of the on-chip buer that is available at the receiver to store previously received packets. This has recently highlighted the importance of HARQ buer management, that is, of the use of buer-aware transmission schemes and of advanced compression policies for the storage of received data. Therefore, in this dissertation, I investigate HARQ buer management by taking an information-theoretic standpoint based on random coding. Specically, standard HARQ schemes, namely Type- I (TI), Chase Combining (CC) and Incremental Redundancy (IR), are rst studied under the assumption of a nite-capacity HARQ buer by considering both coded modulation, via Gaussian signaling, and Bit Interleaved Coded Modulation (BICM). The analysis sheds light on the impact of dierent compression strategies on the throughput. Then, coding strategies based on layered modulation and optimized coding blocklength are investigated, highlighting the benets of HARQ buer-aware transmission schemes. Lastly, the design of compression strategy under multiple-antenna links is studied to show the further throughi put gain. In turn to tackle the above two systems, for an application, I study an edge-based solution that enables a reduction in the latency associated with retransmissions in the downlink of a Distributed-Radio Access Network (D-RAN) system: The RU stores previous transmitted baseband signals, which are encoded by the CU, and retransmits them in case a negative acknowledgement is received, without further processing and without assistance from the CU over the fronthaul link. Based on a nite-blocklength analysis of the throughput and latency, as compared to the conventional D-RAN implementation, the edge-based approach is seen to signicantly reduce the HARQ latency at the cost of a minor reduction in throughput, especially for low-rate transmissions in the presence of slowly varying channels.