A Novel and Efficient Vector Quantization Based CPRI Compression Algorithm

Abstract

The future wireless network, such as the Centralized Radio Access Network (C-RAN), will need to deliver data rate about 100–1000 times the current fourth-generation (4G) technology. For the C-RAN-based network architecture, there is a pressing need for tremendous enhancement of the effective data rate of the common public radio interface (CPRI). Compression of CPRI data is one of the potential enhancements. In this paper, we introduce a vector quantization based compression algorithm for CPRI links, utilizing the Lloyd algorithm. Methods to vectorize the I/Q samples and enhanced initialization of the Lloyd algorithm for codebook training are investigated for improved performance. Multistage vector quantization and unequally protected multigroup quantization are considered to reduce codebook search complexity and codebook size. Simulation results show that our solution can achieve compression of four times for uplink and 4.5 times for downlink, within $2\%$ error vector magnitude (EVM) distortion. Remarkably, vector quantization codebook proves to be quite robust against data modulation mismatch, fading, signal-to-noise ratio (SNR), and Doppler spread.