首页> 外文会议>Information Theory and Applications Workshop (ITA), 2012 >Orthogonal multiple access and information fusion: How many observations are needed?
【24h】

Orthogonal multiple access and information fusion: How many observations are needed?

机译:正交多路访问和信息融合:需要多少个观测值?

获取原文
获取原文并翻译 | 示例

摘要

In this paper, we consider a central estimating officer (CEO) scenario, where sensors observe a noisy version of a binary sequence generated by a single hidden source (the phenomenon). Distributed source coding is not used; rather, the correlation is exploited at the access point (AP), whose goal is to estimate, by properly fusing the data received through AWGN or block fading channels, this sequence. We assume that each node uses a classical channel code to transmit its information to the AP, where decoding is followed by fusion. In the decoding block, joint channel decoding (JCD) or separate channel decoding (SCD) are considered: in the former case, correlation is exploited in the decoding process, whereas in the latter case it is not. We first investigate the ultimate achievable performance limits with JCD (i.e., considering the multiple access channel), in terms of: (i) feasible capacity region in the additive white Gaussian noise (AWGN) channel case; (ii) outage feasible capacity region, in block faded channel case. This analysis provides preliminary insights on the impact of the number of observations. Then, we investigate the overall system performance in terms of bit error rate (BER), probability of outage (only in the block faded case), and probability of decision error (after fusion).
机译:在本文中,我们考虑一个中央估计员(CEO)场景,其中传感器观察到由单个隐藏源(现象)生成的二进制序列的嘈杂版本。不使用分布式源代码。相反,相关性是在接入点(AP)处开发的,其目的是通过适当融合通过AWGN或块衰落信道接收的数据来估计此序列。我们假设每个节点都使用经典的信道代码将其信息传输到AP,然后在解码之后进行融合。在解码块中,考虑联合信道解码(JCD)或单独信道解码(SCD):在前一种情况下,在解码过程中利用了相关性,而在后一种情况下则没有。我们首先根据以下方面研究使用JCD的最终可达到的性能极限(即考虑多路访问信道):( i)加性高斯白噪声(AWGN)信道情况下的可行容量区域; (ii)在块衰落信道情况下,中断可行容量区域。该分析提供了对观测数量影响的初步见解。然后,我们根据误码率(BER),中断概率(仅在块衰落情况下)和决策错误概率(融合之后)研究整个系统的性能。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号