A Statistical Approach to Subspace Based Estimation with Applications in Telecommunications

Subspace based estimation using decomposition techniques such as the SVD is a powerful tool in many signal processing applications where low rank signals in noise are observed. Examples of which include, sensor array signal processing, harmonic analysis, factor analysis, system identification, and blind channel equalization. By appropriately making use of a low rank signal model, subspace based, computationally efficient estimation techniques may be formulated. Also, the performance of subspace based methods is in many cases optimal or near optimal. This paper presents a systematic approach for formulating subspace based estimation techniques based on statistical considerations of the data. This approach may be applied to a wide range of problems where low rank signals are observed in noise. Some special cases are shown to result in well known estimators and examples of subspace based techniques in array signal processing, timing estimation, and channel estimation are given. 1 Introduc..

Adaptive Transmission of Variable-Bit-Rate Video Streams to Mobile Devices

Part 4: Resource Allocation RadioInternational audienceWe propose a novel algorithm to efficiently transmit multiple variable-bit-rate (VBR) video streams from a base station to mobile receivers in wide-area wireless networks. The algorithm transmits video streams in bursts to save the energy of mobile devices. A key feature of the new algorithm is that it dynamically controls the buffer levels of mobile devices receiving different video streams according to the bit rate of the video stream being received by each device. Our algorithm is adaptive to the changes in the bit rates of video streams and allows the base station to transmit more video data on time to mobile receivers. We have implemented the proposed algorithm as well as two other recent algorithms in a mobile video streaming testbed. Our extensive analysis and results demonstrate that the proposed algorithm outperforms two other algorithms and it results in higher energy saving for mobile devices and fewer dropped video frames