Compression and de-compression of complex valued ofdm data for a radio base station

Abstract

A compression method is disclosed, which comprises receiving an OFDM data block comprising a plurality of complex valued data samples wherein each in-phase and quadrature sample value is represented by a first number of bits. The method also comprises calculating an average of absolute sample values of the OFDM data block and mapping the average absolute sample value to a standard deviation value. The method further comprises quantizing each of the sample values using quantization thresholds scaled by the standard deviation value to produce quantized in- phase and quadrature sample value representations, each comprising a second number of bits, and mapping the standard deviation value and the quantized sample value representations to an OFDM transmission frame. Corresponding de-compression method, compressor, de-compressor and network node are also disclosed.

Description

technical field [0001] The present invention relates generally to the field of compression and decompression of data. More specifically, the invention relates to the compression and decompression of complex-valued Orthogonal Frequency Division Multiplexing (OFDM) data for radio base stations. Background technique [0002] In a typical radio base station (RBS), digital and serial internal interfaces establish the connection between the radio equipment control (REC) and the radio equipment (RE) of the RBS. Such an interface is detailed in the specification for the Common Public Radio Interface (CPRI), available at http: / / www.cpri.info / spec.html. For RBS systems supporting Universal Mobile Telecommunications Standard, Long Term Evolution / Long Term Evolution-Advanced (UMTS LTE / LTE-A), complex-valued time-domain OFDM signals are typically transmitted between the remote radio unit (RRU) and baseband unit (BBU) of the RBS through CPRI. ) between transfers. In the user plane info...

AI Technical Summary

Problems solved by technology

Consequently, the average bit length per sample varies from block to block, thus introducing fluctuations into the instantaneously generated data rate, which in turn can cause timing and frame synchronization difficulties

Data rate fluctuations can also exist between antenna paths in multi-antenna applications, which can lead to adverse effects on time alignment between antennas

[0015] Many known techniques for reducing CPRI requirements suffer from one or more disadvantages such as, for example, high complexity, signaling overhead, difficulties in real-time implementation, latency issues, information distortion, limited dynamic range, and difficulty in controlling transmission data rate

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