2009 43rd Annual Conference on Information Sciences and Systems最新文献_第3页

Non-linear coding for improved performance in compressive sensing 改进压缩感知性能的非线性编码

2009 43rd Annual Conference on Information Sciences and Systems Pub Date : 2009-03-18 DOI: 10.1109/CISS.2009.5054682

Yichuan Hu, Zhongmin Wang, J. Garcia-Frías, G. Arce

引用次数: 10

On optimal scheduling for time-division systems with quality of service constraints 具有服务质量约束的分时系统最优调度问题

2009 43rd Annual Conference on Information Sciences and Systems Pub Date : 2009-03-18 DOI: 10.1109/CISS.2009.5054812

A. Balasubramanian, Scott L. Miller

引用次数: 4

Low-complexity index assignments for secure quantization 安全量化的低复杂度指标分配

2009 43rd Annual Conference on Information Sciences and Systems Pub Date : 2009-03-18 DOI: 10.1109/CISS.2009.5054850

João Almeida, G. Maierbacher, J. Barros

引用次数: 1

Asymptotic performance loss in bayesian hypothesis testing under data quantization 数据量化下贝叶斯假设检验的渐近性能损失

2009 43rd Annual Conference on Information Sciences and Systems Pub Date : 2009-03-18 DOI: 10.1109/CISS.2009.5054824

S. Jana

引用次数: 0

Recovery of compressible signals in unions of subspaces 子空间并集中可压缩信号的恢复

2009 43rd Annual Conference on Information Sciences and Systems Pub Date : 2009-03-18 DOI: 10.1109/CISS.2009.5054712

Marco F. Duarte, C. Hegde, V. Cevher, Richard Baraniuk

引用次数: 22

Distributed detection of jamming and defense in wireless sensor networks 无线传感器网络中分布式干扰检测与防御

2009 43rd Annual Conference on Information Sciences and Systems Pub Date : 2009-03-18 DOI: 10.1109/CISS.2009.5054832

Ying Lin, Mingyan Li

引用次数: 13

Energy-efficient modulation design for reliable communication in wireless networks 无线网络中可靠通信的节能调制设计

2009 43rd Annual Conference on Information Sciences and Systems Pub Date : 2009-03-18 DOI: 10.1109/CISS.2009.5054829

Qing Chen, M. C. Gursoy

{"title":"Energy-efficient modulation design for reliable communication in wireless networks","authors":"Qing Chen, M. C. Gursoy","doi":"10.1109/CISS.2009.5054829","DOIUrl":"https://doi.org/10.1109/CISS.2009.5054829","url":null,"abstract":"1 In this paper, we have considered the optimization of the M-ary quadrature amplitude modulation (MQAM) constellation size to minimize the bit energy consumption under average bit error rate (BER) constraints. In the computation of the energy expenditure, the circuit, transmission, and retransmission energies are taken into account. A combined log-normal shadowing and Rayleigh fading model is employed to model the wireless channel. The link reliabilities and retransmission probabilities are determined through the outage probabilities under log-normal shadowing effects. Both single-hop and multi-hop transmissions are considered. Through numerical results, the optimal constellation sizes are identified. Several interesting observations with practical implications are made. It is seen that while large constellations are preferred at small transmission distances, constellation size should be decreased as the distance increases. Similar trends are observed in both fixed and variable transmit power scenarios. We have noted that variable power schemes can attain higher energy-efficiencies. The analysis of energy-efficient modulation design is also conducted in multi-hop linear networks. In this case, the modulation size and routing paths are jointly optimized, and the analysis of both the bit energy and delay experienced in the linear network is provided.","PeriodicalId":433796,"journal":{"name":"2009 43rd Annual Conference on Information Sciences and Systems","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126801728","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: 37

A new idea for addressing multi-objective combinatorial optimization: Quantum multi-agent evolutionary algorithms 多目标组合优化的新思路:量子多智能体进化算法

2009 43rd Annual Conference on Information Sciences and Systems Pub Date : 2009-03-18 DOI: 10.1109/CISS.2009.5054684

Dongming Zhao, Fei Tao

引用次数: 2

Using field data to design a sensor network 利用现场数据设计传感器网络

2009 43rd Annual Conference on Information Sciences and Systems Pub Date : 2009-03-18 DOI: 10.1109/CISS.2009.5054720

S. K. Khandani, M. Kalantari

{"title":"Using field data to design a sensor network","authors":"S. K. Khandani, M. Kalantari","doi":"10.1109/CISS.2009.5054720","DOIUrl":"https://doi.org/10.1109/CISS.2009.5054720","url":null,"abstract":"Distributed sensing and data acquisition in field applications is a labor intensive and expensive process. In such applications, measurements need to be performed in thousands of points. To design a sensor network for soil moisture measurement, we introduce a two step design procedure; in the first step, the data of soil moisture experiments known as SMEX03 (in Little Washita watershed, Oklahoma) is used to approximate the spatial variability of moisture data. Based on the numerical data of SMEX03, the spatial correlation of soil moisture is approximated. Our numerical analysis shows that the spatial correlation of moisture measurements of two points behaves similar to an exponentially decaying function of the distance of those points. The analysis also shows that the moisture measurements for the points with distance up to 150m show a high correlation, while the spatial correlation is practically zero for points that are more than 400m apart. In the second step, we use the spatial correlation of soil moisture to design a sensor network. It is assumed that the sensors are placed sparsely in the field, but it is desirable to estimate the soil moisture at any arbitrary point of the field based on the measurements of the nearby sensors. We use a linear estimator, and give the coefficients that minimize its variance. The value of the minimum variance of the linear estimator depends on the location. We give a closed form formula for the coefficients of the linear minimum variance estimator and the upper bound for the its variance as a function of spatial separation of sensors. Assuming a known value for the maximum allowable moisture estimation variance, we find the optimal placement of the sensors. The results show that in a grid like placement of the sensors in the field, with average separation of distance of 50-100m between neighboring sensor pairs, the soil moisture can be approximated with a good accuracy at any arbitrary point of the field, while increasing the distance of neighboring senors beyond 200m degrades the performance significantly.","PeriodicalId":433796,"journal":{"name":"2009 43rd Annual Conference on Information Sciences and Systems","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115260189","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: 4

Pruning sparse signal models using interference 利用干扰修剪稀疏信号模型

2009 43rd Annual Conference on Information Sciences and Systems Pub Date : 2009-03-18 DOI: 10.1109/CISS.2009.5054763

Bob L. Sturm, J. Shynk, Dae Hong Kim

引用次数: 2