Distributed video coding for wireless video sensor networks: a review of the state-of-the-art architectures

Distributed video coding (DVC) is a relatively new video coding architecture originated from two fundamental theorems namely, Slepian–Wolf and Wyner–Ziv. Recent research developments have made DVC attractive for applications in the emerging domain of wireless video sensor networks (WVSNs). This paper reviews the state-of-the-art DVC architectures with a focus on understanding their opportunities and gaps in addressing the operational requirements and application needs of WVSNs

Accessible Capacity of Secondary Users

A new problem formulation is presented for the Gaussian interference channels (GIFC) with two pairs of users, which are distinguished as primary users and secondary users, respectively. The primary users employ a pair of encoder and decoder that were originally designed to satisfy a given error performance requirement under the assumption that no interference exists from other users. In the scenario when the secondary users attempt to access the same medium, we are interested in the maximum transmission rate (defined as {\em accessible capacity}) at which secondary users can communicate reliably without affecting the error performance requirement by the primary users under the constraint that the primary encoder (not the decoder) is kept unchanged. By modeling the primary encoder as a generalized trellis code (GTC), we are then able to treat the secondary link and the cross link from the secondary transmitter to the primary receiver as finite state channels (FSCs). Based on this, upper and lower bounds on the accessible capacity are derived. The impact of the error performance requirement by the primary users on the accessible capacity is analyzed by using the concept of interference margin. In the case of non-trivial interference margin, the secondary message is split into common and private parts and then encoded by superposition coding, which delivers a lower bound on the accessible capacity. For some special cases, these bounds can be computed numerically by using the BCJR algorithm. Numerical results are also provided to gain insight into the impacts of the GTC and the error performance requirement on the accessible capacity.Comment: 42 pages, 12 figures, 2 tables; Submitted to IEEE Transactions on Information Theory on December, 2010, Revised on November, 201

Implementable Wireless Access for B3G Networks - III: Complexity Reducing Transceiver Structures

This article presents a comprehensive overview of some of the research conducted within Mobile VCE’s Core Wireless Access Research Programme,1 a key focus of which has naturally been on MIMO transceivers. The series of articles offers a coherent view of how the work was structured and comprises a compilation of material that has been presented in detail elsewhere (see references within the article). In this article MIMO channel measurements, analysis, and modeling, which were presented previously in the first article in this series of four, are utilized to develop compact and distributed antenna arrays. Parallel activities led to research into low-complexity MIMO single-user spacetime coding techniques, as well as SISO and MIMO multi-user CDMA-based transceivers for B3G systems. As well as feeding into the industry’s in-house research program, significant extensions of this work are now in hand, within Mobile VCE’s own core activity, aiming toward securing major improvements in delivery efficiency in future wireless systems through crosslayer operation

Activity recognition from videos with parallel hypergraph matching on GPUs

In this paper, we propose a method for activity recognition from videos based on sparse local features and hypergraph matching. We benefit from special properties of the temporal domain in the data to derive a sequential and fast graph matching algorithm for GPUs. Traditionally, graphs and hypergraphs are frequently used to recognize complex and often non-rigid patterns in computer vision, either through graph matching or point-set matching with graphs. Most formulations resort to the minimization of a difficult discrete energy function mixing geometric or structural terms with data attached terms involving appearance features. Traditional methods solve this minimization problem approximately, for instance with spectral techniques. In this work, instead of solving the problem approximatively, the exact solution for the optimal assignment is calculated in parallel on GPUs. The graphical structure is simplified and regularized, which allows to derive an efficient recursive minimization algorithm. The algorithm distributes subproblems over the calculation units of a GPU, which solves them in parallel, allowing the system to run faster than real-time on medium-end GPUs

TTCM-aided rate-adaptive distributed source coding for Rayleigh fading channels

Adaptive turbo-trellis-coded modulation (TTCM)-aided asymmetric distributed source coding (DSC) is proposed, where two correlated sources are transmitted to a destination node. The first source sequence is TTCM encoded and is further compressed before it is transmitted through a Rayleigh fading channel, whereas the second source signal is assumed to be perfectly decoded and, hence, to be flawlessly shown at the destination for exploitation as side information for improving the decoding performance of the first source. The proposed scheme is capable of reliable communications within 0.80 dB of the Slepian-Wolf/Shannon (SW/S) theoretical limit at a bit error rate (BER) of 10-5. Furthermore, its encoder is capable of accommodating time-variant short-term correlation between the two sources