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Cognitive Code-Division Multiplexing and Generalized-polygon-based Coding.

机译：认知码分复用和基于广义多边形的编码。

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摘要

In the last decade, wireless communication service has experienced explosive growth while communication technologies have progressed generation by generation. Code-division multiplexing (CDM) or code-division multiple-access (CDMA) is seen as a promising basic technology for 3G/4G cellular communications or cognitive radio networks. The first part of this work is to investigate the problem of cognitive code-division multiplexing. We propose a cognitive code-division framework that allows secondary users to share the spectrum with a primary CDMA system. This framework provides flexibility to allocate transmitting power and real-valued code sequence of the secondary channel that maximize the signal-to-interference-plus-noise ratio (SINR) of the secondary user and in the meantime ensure the SINR requirements of all primary channels. This is shown to be a non-convex NP-hard optimization problem. A novel algorithm is provided that returns a desirable suboptimum solution by using semidefinite programming. To facilitate the implementation, we study the problem of designing binary signatures (spreading codes) in direct-sequence code-division multiple-access (DS-CDMA) systems. Our objective is to find the binary signature that maximizes the signal-to-interference-plus-noise (SINR) at the output of maximum-SINR (MSINR) linear filter. However, the maximization problem over the binary field is NP-hard with complexity exponential in the signature length. We present a low-complexity search algorithm that outputs the desirable binary solution with the deterministic SINR performance guarantee. Furthermore, we derive easy to calculate upper and lower bounds on the SINR of the optimal binary and quaternary sequences that can serve as a benchmark for any suggested suboptimal designs.;Channel coding in wireless communications plays a key role because of uncertainty of channel fading and noise. The secondary part of this work is to investigate generalized-polygon-based (GP-based) coding. The performance of a GP-LDPC code under iterative decoding over binary erasure channels is determined by the stopping distance of the associated Tanner graph. Unfortunately, it has been proved that the problem of finding the stopping distance of a given LDPC code is NP-hard. It is well-known that the stopping distance is upper-bounded by the minimum distance. We derive new lower bounds on the stopping distance of LDPC codes generated from generalized polygons. Compressed sensing emerges as a promising technology to efficiently reduce the sampling rate for sparse signals. There exists a very close relationship between CS and error-correcting codes over large discrete alphabets. We propose new deterministic low-storage constructions of compressive sampling matrices based on classical finite-geometry generalized polygons. We also develop novel recovery algorithms for sparse signals under the noiseless and noisy environments.
机译：在过去的十年中，无线通信服务经历了爆炸性的增长，而通信技术却一代又一代地发展。码分复用（CDM）或码分多址（CDMA）被视为3G / 4G蜂窝通信或认知无线电网络的有前途的基本技术。这项工作的第一部分是研究认知码分复用的问题。我们提出了一种认知代码划分框架，该框架允许次要用户与主要CDMA系统共享频谱。该框架提供了灵活性，可以分配辅助信道的发射功率和实值码序列，从而最大程度地提高辅助用户的信噪比（SINR），同时确保所有主要信道的SINR要求。这显示为非凸NP硬优化问题。提供了一种新颖的算法，该算法通过使用半定编程来返回理想的次优解。为了便于实现，我们研究了在直接序列码分多址（DS-CDMA）系统中设计二进制签名（扩展码）的问题。我们的目标是在最大SINR（MSINR）线性滤波器的输出端找到能够最大化信噪比（SINR）的二进制签名。但是，二进制字段上的最大化问题是NP难的，签名长度的复杂度呈指数增长。我们提出了一种低复杂度的搜索算法，该算法输出具有确定性SINR性能保证的理想二进制解决方案。此外，我们得出易于计算的最佳二进制和四进制序列的SINR上限和下限，可以用作任何建议的次优设计的基准。；由于信道衰落和不确定性，无线通信中的信道编码起着关键作用。噪声。这项工作的第二部分是研究基于通用多边形（基于GP）的编码。在二进制擦除通道上进行迭代解码时，GP-LDPC码的性能取决于相关的Tanner图的停止距离。不幸的是，已经证明找到给定的LDPC码的停止距离的问题是NP困难的。众所周知，停止距离以最小距离为上限。我们推导了从广义多边形生成的LDPC码的停止距离的新下限。压缩感测是一种有前途的技术，可以有效降低稀疏信号的采样率。在大的离散字母上，CS和纠错码之间存在非常密切的关系。我们提出了基于经典有限几何广义多边形的压缩采样矩阵的新确定性低存储构造。我们还开发了新颖的恢复算法，可在无噪声和嘈杂的环境下处理稀疏信号。

著录项

  • 作者

    Gao, Kanke.;

  • 作者单位

    State University of New York at Buffalo.;

  • 授予单位 State University of New York at Buffalo.;
  • 学科 Engineering Electronics and Electrical.
  • 学位 Ph.D.
  • 年度 2012
  • 页码 110 p.
  • 总页数 110
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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