International audienceMost source coding standards (voice, audio, image and video) use Variable-Length Codes (VLCs) for compression. However, the VLC decoder is very sensitive to transmission errors in the compressed bit-stream. Previous contributions, using a trellis description of the VLC codewords to perform soft decoding, have been proposed. Significant improvements are achieved bythis approach when compared with prefix decoding. Nevertheless,for realistic VLCs, the complexity of the trellis technique becomesintractable. In this paper, we propose a soft-input VLC decodingmethod using an a priori knowledge of the lengths of the sourcesymbolsequence and the compressed bit-stream with Maximum A Posteriori (MAP) sequence estimation. Performance in the case of transmission over an Additive White Gaussian Noise (AWGN)channel is evaluated. Simulation results show that the proposed decoding algorithm leads to significant performance gain incomparison with the prefix VLC decoding besides exhibiting very low complexity. A new VLC decoding method generating additional information regarding the reliability of the bits of the compressed bit-stream is also proposed. We consider the serial concatenation of a VLC with two types of channel code and perform iterative decoding. Results show that, when concatenated with a recursive systematic convolutional code (RSCC), iterativedecoding provides remarkable error correction performance.In fact, a gain of about 2.3 dB is achieved, in the case of transmission over an AWGN channel, with respect to tandem decoding. Second, we consider a concatenation with a low-density parity-check (LDPC) code and it is shown that iterative joint source/channel decoding outperforms tandem decoding and an additional coding gain of 0.25 dB is achieved

International audienceCentralized/Cloud Radio Access Network (C-RAN) is a promising future mobile network architecture, which can potentially increase the capacity of mobile network meanwhile reducing operators' cost. In standard C-RAN, frequency shifting is made in Remote Radio Heads (RRHs), which are close to the antennas. Signal processing and upper layers are made in Baseband Unit (BBU) pool for multiple base stations. However, this results in high burden on the optical transport network between RRHs and BBU pool. This paper investigates new functional split architectures between RRH and BBU, to reduce the transmission throughput between RRHs and BBUs. Two new architectures are proposed and modeled for the uplink. We propose to move part of physical layer functions of the BBU to the RRH. For the proposed architectures, the transmission rate between RRHs and BBUs depends on the mobile network load, while that of current architecture is constant. Simulation results illustrate that 30 to 40 percent bandwidth can be saved when all the radio channel capacity is used, and up to 70 percent bandwidth when half of the radio channel capacity is used