TY - JOUR
T1 - Adaptive Compression and Joint Detection for Fronthaul Uplinks in Cloud Radio Access Networks
AU - Vu, Thang X.
AU - Nguyen, Hieu D.
AU - Quek, Tony Q.S.
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/11
Y1 - 2015/11
N2 - Cloud radio access network (C-RAN) has recently attracted much attention as a promising architecture for future mobile networks to sustain the exponential growth of data rate. In C-RAN, one data processing center or baseband unit (BBU) communicates with users via distributed remote radio heads (RRHs), which are connected to the BBU via high capacity, low latency fronthaul links. In this paper, we study the compression on fronthaul uplinks and propose a joint decompression algorithm at the BBU. The central premise behind the proposed algorithm is to exploit the correlation between RRHs. Our contribution is threefold. First, we propose a joint decompression and detection (JDD) algorithm which jointly performs decompressing and detecting. The JDD algorithm takes into consideration both the fading and compression effect in a single decoding step. Second, block error rate (BLER) of the proposed algorithm is analyzed in closed-form by using pair-wise error probability analysis. Third, based on the analyzed BLER, we propose adaptive compression schemes subject to quality of service (QoS) constraints to minimize the fronthaul transmission rate while satisfying the pre-defined target QoS. As a dual problem, we also propose a scheme to minimize the signal distortion subject to fronthaul rate constraint. Numerical results demonstrate that the proposed adaptive compression schemes can achieve a compression ratio of 300% in experimental setups.
AB - Cloud radio access network (C-RAN) has recently attracted much attention as a promising architecture for future mobile networks to sustain the exponential growth of data rate. In C-RAN, one data processing center or baseband unit (BBU) communicates with users via distributed remote radio heads (RRHs), which are connected to the BBU via high capacity, low latency fronthaul links. In this paper, we study the compression on fronthaul uplinks and propose a joint decompression algorithm at the BBU. The central premise behind the proposed algorithm is to exploit the correlation between RRHs. Our contribution is threefold. First, we propose a joint decompression and detection (JDD) algorithm which jointly performs decompressing and detecting. The JDD algorithm takes into consideration both the fading and compression effect in a single decoding step. Second, block error rate (BLER) of the proposed algorithm is analyzed in closed-form by using pair-wise error probability analysis. Third, based on the analyzed BLER, we propose adaptive compression schemes subject to quality of service (QoS) constraints to minimize the fronthaul transmission rate while satisfying the pre-defined target QoS. As a dual problem, we also propose a scheme to minimize the signal distortion subject to fronthaul rate constraint. Numerical results demonstrate that the proposed adaptive compression schemes can achieve a compression ratio of 300% in experimental setups.
UR - http://www.scopus.com/inward/record.url?scp=84960077660&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84960077660&partnerID=8YFLogxK
U2 - 10.1109/TCOMM.2015.2475430
DO - 10.1109/TCOMM.2015.2475430
M3 - Article
AN - SCOPUS:84960077660
VL - 63
SP - 4565
EP - 4575
JO - IEEE Transactions on Communications
JF - IEEE Transactions on Communications
SN - 1558-0857
IS - 11
M1 - 7234851
ER -