An LPC-Based Fronthaul Compression Scheme

Abstract

Several new architectures are under investigation for cloud radio access networks, assuming distinct splits of functionality among the network elements. Consequently, the research on radio data compression for the fronthaul is based on assumptions that correspond to a wide variety of tradeoffs among data rate, signal distortion, latency and computational cost. This paper describes a method for LTE downlink point-topoint signal compression based on linear prediction and Huffman coding, which is suitable for low cost encoding and decoding units with stringent restrictions on power consumption. The proposed method can work at various compression factors, such as 3.3:1 at an average EVM of 0.9%, or 4:1 at an average EVM of 2.1%.

Improved LPC-Based Fronthaul Compression With High Rate Adaptation Resolution

“…The proposed method is based on the scheme of [5], which encodes real (s i ) and imaginary (s q ) baseband components independently. This work assumes the RRU is capable of extracting the symbol timing synchronism and the cyclic prefix (CP) can be conveniently removed.…”

“…As proposed in [5], the P initial samples of each OFDM symbol x[n] are sent uncompressed over the FH (switches of Fig. 1 in position 1).…”

“…1 in position 1). This allows the decoder to initialize the P taps of the predictor A(z) (see [5]) before starting the compression and, by doing so, avoid increased prediction errors at the OFDM symbol boundaries. In the end, the effective average compression factor becomes F = …”

“…one that has not passed through a channel. First, the predictor design is conducted as proposed in [5], where the predictor coefficients are calculated according to the Levinson-Durbin algorithm [6] and the autocorrelation function of the training signal. Then, the open loop prediction errors are computed by…”

“…The new FSC scheme derives from an earlier work [5] and is based on a combination of LPC adapted to orthogonal frequency division multiplexing (OFDM), being further improved here with adjustable scaling. It will be shown that the scaling creates a mechanism to achieve finer resolution in the adjustments to the compression factor and distortion.…”