A new IQ data compression scheme for front-haul link in Centralized RAN

Nanba, Shinobu; Agata, A.

doi:10.1109/pimrcw.2013.6707866

Cited by 46 publications

(33 citation statements)

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“…Numerical results show that compression ratio of 400% can be achieved by the proposed optimization scheme, i.e., the proposed adaptive compression scheme can support four times more number of RRHs than the fixed compression scheme. A possibly higher compression ratio is also achievable by combining the proposed scheme with control-signal compression techniques [5][6][7]. Such extensions will be considered in subsequent studies.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

“…Various compression techniques have been proposed to reduce the fronthaul transmission rate in both time and frequency domains via, e.g., sub-carrier compression [1], [5][6][7]. Good compression ratio is achieved thanks to the reduction of control information redundancy in Common Public Radio Interface (CPRI) structure -introduced in [8].…”

Section: Introductionmentioning

confidence: 99%

“…Good compression ratio is achieved thanks to the reduction of control information redundancy in Common Public Radio Interface (CPRI) structure -introduced in [8]. In [5], [6], lossless compression is proposed which optimizes the redundancy in both time and frequency domains and in turn achieves good compression gain. Such improvement is the result from: i) only information data of active users are transmitted on fronthaul links, ii) a large amount of control information is locally generated, and iii) a reduced set of precoding matrix is transferred.…”

Section: Introductionmentioning

confidence: 99%

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Joint Decoding and Adaptive Compression with QoS Constraint for Uplinks in Cloud Radio Access Networks

Quek

Nguyen

2015

2015 IEEE Global Communications Conference (GLOBECOM)

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Abstract-Cloud Radio Access Network (C-RAN) is a promising candidate for future mobile networks to sustain the exponentially increasing demand for data rate. The centralized architecture enables C-RAN to exploit multi-cell cooperation and interference management effectively. In C-RAN, one baseband unit (BBU) communicates with users through distributed Remote Radio Heads (RRHs) which are connected to the BBU via high capacity, low latency fronthaul links and perform "soft" relaying. However, the architecture of C-RAN imposes a shortage of fronthaul bandwidth because raw In-phase/Quadrature-phase (I/Q) samples are exchanged between the RRHs and the BBU. In this paper, we leverage on advanced signal processing to improve the compression efficiency in fronthaul uplinks. Specifically, we propose a joint decoding algorithm at the BBU that exploits the correlation among the RRHs and jointly performs decompressing and decoding. An upper bound of the Block Error Rate (BLER) of the proposed algorithm is derived using pair-wise error probability analysis. Based on the BLER upper bound, we propose an adaptive compression scheme which minimizes the fronthaul transmission rate while satisfying a target quality of service constrain on the BLER. Our proposed adaptive compressor originates from practical scenarios in which most applications tolerate certain non-zero BLER thresholds.Index Terms-Cloud radio access network, joint decompression and decoding, adaptive compression, transmission error probability.

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Section: Conclusion and Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Joint Decoding and Adaptive Compression with QoS Constraint for Uplinks in Cloud Radio Access Networks

Quek

Nguyen

2015

2015 IEEE Global Communications Conference (GLOBECOM)

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“…Numerous research efforts have recently investigated the compression of C-RAN, from both information-theoretic perspective [5][6][7][8], which designs and optimizes the quantization noise to maximize the achievable sum rate, and practical system point of view [11], [12], which minimizes redundancy of control information in common public radio interface package. It is shown, in general, that the joint design of the precoding and quantization noise matrix can significantly improve the system sum rate over separate designs [5].…”

Section: Introductionmentioning

confidence: 99%

“…From the practical system perspective, efficient compression can be performed in both time-and frequencydomains (sub-carrier compression) [1]. Lossless compression is proposed to achieve a good statistical multiplexing gain with a negligible signal distortion [11], [12]. In this compression strategy, only data of active users are transferred on the fronthauls and a maximum amount of control informations are locally generated.…”

Section: Introductionmentioning

confidence: 99%

Fronthaul compression and optimization for cloud radio access networks

Nguyen

Quek

et al. 2016

2016 IEEE International Conference on Communications (ICC)

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Abstract-In the present paper, we investigate the design and optimization for fronhaul links in cloud radio access networks (C-RAN). Existing C-RAN designs rely on the instantaneous network-wide channel state information (CSI), which might impose a significant overhead due to the potential large-scale of C-RAN. To overcome this limitation, we optimize C-RAN based on the average performance metrics which only require the second-order statistics of the fading channels. Firstly, a tight upper bound of the block error rate (BLER) over Rayleigh fading channels is derived in closed-form expression, through which some insights on C-RAN are drawn: i) full diversity order, which is equal to the number of RRHs, is achievable with respect to the signal to compression plus noise ratio; and ii) the BLER is limited below by either compression or Gaussian noises. Secondly, based on the derived bound, a compression optimization is proposed to minimize the fronthaul transmission rate while satisfying some predefined BLER constraints. The premise of the proposed optimization originates from practical scenarios where most applications tolerate a non-zero BLER. Finally, a fronthaul rate allocation scheme is proposed to minimize the system BLER. It is proved that the proposed allocation scheme, which imposes uniform compression noise across the RRHs, approaches the optimal allocation as the total fronthauls' bandwidth increases.

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