2008 42nd Asilomar Conference on Signals, Systems and Computers最新文献_第4页

Objective analysis of temporally varying audio quality metrics 客观分析时间变化的音频质量指标

2008 42nd Asilomar Conference on Signals, Systems and Computers Pub Date : 2008-10-01 DOI: 10.1109/ACSSC.2008.5074616

Joseph C. Hardin, C. Creusere

引用次数: 8

Compressed sensing and robust recovery of low rank matrices 低秩矩阵的压缩感知与鲁棒恢复

2008 42nd Asilomar Conference on Signals, Systems and Computers Pub Date : 2008-10-01 DOI: 10.1109/ACSSC.2008.5074571

Maryam Fazel, E. Candès, B. Recht, P. Parrilo

引用次数: 126

Doppler measurements rendering random routing 多普勒测量显示随机路由

2008 42nd Asilomar Conference on Signals, Systems and Computers Pub Date : 2008-10-01 DOI: 10.1109/ACSSC.2008.5074539

Liang Dong

引用次数: 0

New protocols for the cooperative MAC 合作MAC的新协议

2008 42nd Asilomar Conference on Signals, Systems and Computers Pub Date : 2008-10-01 DOI: 10.1109/ACSSC.2008.5074559

Charlotte Hucher, G. R. Othman, A. Saadani

引用次数: 1

Gaussian fading interference channels: Power control 高斯衰落干扰信道:功率控制

2008 42nd Asilomar Conference on Signals, Systems and Computers Pub Date : 2008-10-01 DOI: 10.1109/ACSSC.2008.5074498

Daniela Tuninetti

引用次数: 31

Extension of the Reed-Mallett-Brennan loss for application to stap with collected data 延长Reed-Mallett-Brennan损失申请与收集的数据同步

2008 42nd Asilomar Conference on Signals, Systems and Computers Pub Date : 2008-10-01 DOI: 10.1109/ACSSC.2008.5074712

C. M. Teixeira

{"title":"Extension of the Reed-Mallett-Brennan loss for application to stap with collected data","authors":"C. M. Teixeira","doi":"10.1109/ACSSC.2008.5074712","DOIUrl":"https://doi.org/10.1109/ACSSC.2008.5074712","url":null,"abstract":"The post-processed signal-to-interference-plus-noise ratio (SINR) has emerged as a critical performance metric in the assessment of space-time adaptive processing (STAP) as applied to radar data collected from multidimensional arrays. In their seminal analysis, Reed, Mallett and Brennan analytically characterized the loss in SINR (ldquoRMB lossrdquo) realized due to the use of an estimate of the interference environment with a finite set of samples relative to the exact result under certain conditions. While providing several well-known ldquorules-of-thumbrdquo that allows the RMB loss to be incorporated into system level analysis, this original formulation can not generally be directly applied to collected radar data since it assumes knowledge of the exact interference covariance which typically is not available. In this paper, the RMB loss is extended to the practical situation where the exact covariance is not available, as with collected radar data. As a consequence, both the adaptive weight and residual interference-plus-noise power must be estimated in computing SINR. Three new approaches for accomplishing this are analyzed and compared in terms of their theoretically derived probability distribution functions, means and variances relative to each other as well as the original RMB loss result. The developed theory is extensively verified with simulation results. A key result is the need for two independent sets of training data to accurately compute the SINR when sample support is limited. New rules-of-thumb are suggested for the amount of training data needed from these two sets of data (i.e. two groups of local range data) to achieve an accurate assessment of SINR loss. This work provides new analytical tools that can be used to better understand the true SINR loss performance of STAP with collected radar data.","PeriodicalId":416114,"journal":{"name":"2008 42nd Asilomar Conference on Signals, Systems and Computers","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128406925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

MIMO radar detection of targets in compound-Gaussian clutter 复合高斯杂波条件下MIMO雷达目标检测

2008 42nd Asilomar Conference on Signals, Systems and Computers Pub Date : 2008-10-01 DOI: 10.1109/ACSSC.2008.5074393

M. Akçakaya, M. Hurtado, A. Nehorai

引用次数: 22

Overcoming polar-format issues in multichannel SAR Autofocus 克服多通道SAR自动对焦中极化格式问题

2008 42nd Asilomar Conference on Signals, Systems and Computers Pub Date : 2008-10-01 DOI: 10.1109/ACSSC.2008.5074460

Hyun Jeong Cho, D. Munson

引用次数: 16

Two-way relaying with network coding for frequency-selective fading channels 频率选择性衰落信道的网络编码双向中继

2008 42nd Asilomar Conference on Signals, Systems and Computers Pub Date : 2008-10-01 DOI: 10.1109/ACSSC.2008.5074830

T. Koike-Akino, P. Popovski, V. Tarokh

引用次数: 5

Design and architecture of spatial multiplexing MIMO decoders for FPGAs fpga空间复用MIMO解码器的设计与结构

2008 42nd Asilomar Conference on Signals, Systems and Computers Pub Date : 2008-10-01 DOI: 10.1109/ACSSC.2008.5074383

C. Dick, K. Amiri, Joseph R. Cavallaro, R. Rao

{"title":"Design and architecture of spatial multiplexing MIMO decoders for FPGAs","authors":"C. Dick, K. Amiri, Joseph R. Cavallaro, R. Rao","doi":"10.1109/ACSSC.2008.5074383","DOIUrl":"https://doi.org/10.1109/ACSSC.2008.5074383","url":null,"abstract":"Spatial multiplexing multiple-input-multiple-output (MIMO) communication systems have recently drawn significant attention as a means to achieve tremendous gains in wireless system capacity and link reliability. The optimal hard decision detection for MIMO wireless systems is the maximum likelihood (ML) detector. ML detection is attractive due to its superior performance (in terms of BER). However, direct implementation grows exponentially with the number of antennas and the modulation scheme, making its ASIC or FPGA implementation infeasible for all but low-density modulation schemes using a small number of antennas. Sphere decoding (SD) solves the ML detection problem in a computationally efficient manner. However, even with this complexity reduction, real-time implementation on a DSP processor is generally not feasible and high-performance parallel computing platforms such as FPGAs are increasingly being employed for this class of applications. The sphere detection problem affords many opportunities for algorithm and micro-architecture optimizations and tradeoffs. This paper provides an overview of techniques to simplify and minimize FPGA resource utilization of sphere detectors for high-performance low-latency systems.","PeriodicalId":416114,"journal":{"name":"2008 42nd Asilomar Conference on Signals, Systems and Computers","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129451680","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 11