Bandwidth scaling for efficient inference over a power-limited MAC

被引：0

作者：

Marano, Stefano ^{[1
]}

Matta, Vincenzo ^{[1
]}

Tong, Lang ^{[2
]}

Willett, Peter ^{[3
]}

机构：

[1] Univ Salerno, DIIIE, Via Ponte Melillo, I-84084 Fisciano, SA, Italy

[2] Cornell Univ, ECE Dept, Ithaca, NY 14853 USA

[3] Univ Connecticut, ECE Dept, Storrs, CT 06269 USA

来源：

2007 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOL III, PTS 1-3, PROCEEDINGS | 2007年

关键词：

wireless sensor network; multiple access; multiterminal inference; TBMA;

D O I：

暂无

中图分类号：

O42 [声学];

学科分类号：

070206 ; 082403 ;

摘要：

We introduce a Likelihood Based Multiple Access (LBMA) communication/estimation scheme for nonrandom parameter estimation in wireless sensor networks with additive multiple access channels. Constraining the system in terms of energy and allowing the available number of degrees of freedom to scale as n(alpha), 0.5 < alpha < 1, we prove that LBMA is asymptotically efficient. Thus, the new scheme is appropriate for large networks. LBMA is, in addition, simple to implement and relies upon an intuitive approach.

引用

页码：597 / +

页数：2

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