Joint Decompression and Decoding for Cloud Radio Access Networks
Joint Decompression and Decoding for Cloud Radio Access Networks
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DOI：
10.1109/lsp.2013.2253095
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发表时间：
2013-05-01
影响因子：
3.9
通讯作者：
Shamai (Shitz), Shlomo
中科院分区：
文献类型：
--
作者：
Park, Seok-Hwan;Simeone, Osvaldo;Shamai (Shitz), Shlomo
针对多天线云无线接入网上行链路，研究了联合解压缩和解码技术。在该系统中，一组多天线移动的站（MS）希望通过一组多天线基站（BS）与“云”解码器通信，所述多天线基站（BS）通过有限容量的数字回程链路连接到云解码器。BS压缩接收到的信号并将其发送到云解码器，云解码器执行来自所有MS的信号的联合解码。虽然传统的解决方案规定云解码器首先执行解压缩，然后执行解码，但最近的工作已经表明，在云解码器处可以利用联合解压缩和解码（JDD）来实现潜在的更大速率。在高斯测试信道的假设下，JDD的和速率最大化问题在这里被证明是一类称为凸差（DC）问题的非凸问题的一个实例。基于这一观察，提出了一种基于优化最小化（MM）方法的迭代算法，保证收敛到一个稳定点的和速率最大化问题。数值结果表明，该算法的优势相比，传统的方法，基于单独的解压缩和解码。
In this work, joint decompression and decoding is studied for the uplink of multi-antenna cloud radio access networks. In this system, a set of multi-antenna mobile stations (MSs) wish to communicate with a "cloud" decoder through a set of multi-antenna base stations (BSs), which are connected to the cloud decoder through digital backhaul links of limited capacity. The BSs compress the received signal and send it to the cloud decoder, which performs joint decoding of the signals from all MSs. While the conventional solution prescribes that the cloud decoder performs first decompression and then decoding, recent work has shown that potentially larger rates can be achieved with joint decompression and decoding (JDD) at the cloud decoder. The sum-rate maximization problem with JDD, under the assumption of Gaussian test channels, is shown here to be an instance of a class of non-convex problems known as Difference of Convex (DC) problems. Based on this observation, an iterative algorithm based on the Majorization Minimization (MM) approach is proposed that guarantees convergence to a stationary point of the sum-rate maximization problem. Numerical results demonstrate the advantage of the proposed algorithm compared to the conventional approach based on separate decompression and decoding.