In this paper, we develop Prioritized Adaptive Code-Enhanced (PACE) link-layer protocol to achieve preferred data recovery order across connections, while maintaining stable and reliable data flow over a wireless network. We classify link-layer traffic arrivals into different priorities based on delay constraint and distortion associated with that traffic. We formulate the link-layer buffer as a multiclass M/G/1 priority queuing system and the decoding process by a nonhomogeneous Geometric density function. This formulation enables the determination of an optimal dynamic decoder scheduling for heterogeneous link-layer traffic. PACE employs rate-adaptive Low Density Parity Check (LDPC) codes for error recovery. We demonstrate experimentally that PACE reduces the throughput-delay cost by 20%-70% in comparison with the IEEE802.11 ARQ and Hybrid ARQ (HARQ) protocols. Further, it achieves 20%-60% throughput and 2-10dB PSNR improvements in channel bandwidth utilization and realtime video playback quality.

Pre-/post-processing filters obtained from lapped transforms achieve higher coding efficiency by exploiting transform block boundary correlation. Existing approaches however do not explicitly consider the impact of pre-filtering on prediction efficiency, thereby resulting in a lower overall rate-distortion performance. We present a framework where filters are designed with an objective function based on a prediction model. The post-filter is constructed so as to reverse the pre-filter processing at the decoder. We show how the pre-filters thus derived can be refined and local adaptation parameters obtained for better compression efficiency. To further enhance the performance, the mode decision is altered by separating the contribution of luma and chroma components in the rate-distortion model. The overall system performance is measured using a weighted Bjontegaard delta bitrate, showing an overall saving of 2.58% to 6.78% with respect to the “Key Technical Area” (KTA) codec. Additionally, the designed filters significantly reduce the blocking artifacts observed in KTA.

Network coding (NC) within wireless sensor networks (WSNs) can be viewed as the mapping of efficient channel codes to the data generated within the network. In particular, this perspective of code-on-network-graphs (CNG) can be exploited to map source data generated within WSN (of size K) to a variable nodes subset in low-density parity check (LDPC) codes. The resulting fixed size symbol stream when transmitted through the network suffers erasures. At sink, an average ofzsource symbols can be recovered by employing belief propagation decoding. In this paper, we determine CNG code ensembles that achieve maximal recovery (z/K) for different erasure rates and network topological constraints corresponding to node transmission range. An analytic framework to predict code performance under transmission range constraints is developed. Additionally, necessary condition for code stability was derived using fixed-point stability analysis. Optimal solutions for a WSN with 1000 nodes are determined using differential evolution algorithm. We outline a distributed algorithm for generating a sequence of encoded symbols adhering to the designed code ensemble. The performance of the designed CNG code is demonstrated to be superior to random NC and growth code based ensembles, as well as resilient to network size and inter-connectivity variations.

One of the key factors underlying the popularity of Low-density parity-check (LDPC) code is its iterative decoding algorithm that is amenable to efficient hardware implementation. Even though different variants of LDPC iterative decoding algorithms have been studied for its error-correcting properties, an analytical basis for evaluating energy efficiency of LDPC decoders has not been reported. In this paper, we present a framework of a parameterized LDPC decoding algorithm that can be optimized to produce sparse representation of communication messages used in iterative decoding. The sparsity of messages is determined by its differential entropy and has been used as a theoretical metric for determining the energy efficiency of an iterative LDPC decoder. At the core of the proposed algorithm is margin propagation (MP) which approximates the log-sum-exp function used in conventional sum-product (SP) decoders by a piecewise linear (PWL) function. Using Monte-Carlo simulations, we demonstrate that the MP decoding leads to a significant reduction in message entropy compared to a conventional SP decoder, while incurring a negligible performance penalty (less than 0.03 dB). The proposed work therefore lays the foundation for design of parameterized LDPC decoders whose bit-error-rate performance can be effectively traded-off with respect to different energy efficiency constraints as required by different set of applications.

In this paper we describe a practical implementation of a distributed video codec deployed on a real visual sensor platform, viz. the MicaZ/Cyclops platform. The codec supports two encoding schemes, one employs Discrete Cosine Transform (DCT) and the other operates on raw pixels. DCT scheme is more costly in terms of computational power consumption, on the other hand it leads to more compression and hence less transmission power consumption. At the same time the DCT scheme may not necessarily achieve minimal overall power consumption (computation and transmission). In this paper we show that the choice of either scheme (DCT or pixel based) depends on the tolerable distortion and power consumption. Results show that for a range of achievable video quality values the DCT scheme demonstrates less overall power consumption. On the other hand for another range of video quality the pixel scheme results in less overall power consumption.

Real-time video communication over wireless channels is subject to information loss since wireless links are error-prone and susceptible to noise. Popular wireless link-layer protocols, such as retransmission (ARQ) based 802.11 and hybrid ARQ methods provide some level of reliability while largely ignoring the latency issue which is critical for real-time applications. Therefore, they suffer from low throughput (under high-error rates) and large waiting-times leading to serious degradation of video playback quality. In this paper, we develop an analytical framework for video communication which captures the behavior of real-time video traffic at the wireless link-layer while taking into consideration both reliability and latency conditions. Using this framework, we introduce a delay constraint packet embedded error control (DC-PEEC) protocol for wireless link-layer. DC-PEEC ensures reliable and rapid delivery of video packets by employing various channel codes to minimize fluctuations in throughput and provide timely arrival of video. In addition to theoretically analyzing DC-PEEC, the performance of the proposed scheme is analyzed by simulating real-time video communication over ldquorealrdquo channel traces collected on 802.11 b WLANs using H.264/AVC JM14.0 video codec. The experimental results demonstrate performance gains of 5-10 dB for different real-time video scenarios.

In pixel-domain distributed video coding (DVC), due to the largely translational nature of motion, residue errors in the side-information frame are often clustered together. These clusterings can be exploited to reduce the number of syndrome bits required to successfully perform low density parity check (LDPC) decoding, and therefore improve the overall rate-distortion performance. We shall see that using alternate iterations of LDPC syndrome decoding and Baum-Welch channel estimation proves to be an efficient scheme for exploiting the spatial clustering of errors in pixel-domain DVC. In this paper we demonstrate that a sparser power-law based scheduling of the channel estimation iteration leads to significant reduction in estimation complexity (around 83% reduction) for a small loss in rate-distortion performance (less than 0.75 dB). This sparser scheduling of channel estimation iterations can potentially improve decoding delays.

Recent advances have shown that channel codes can be mapped onto networks to realize efficient Network Coding (NC); this has led to the emergence of Code-on-Network-Graphs (CNG). Traditional CNG approaches (e.g Decentralized Erasure Codes) focus on a generating a sequence of encoded symbols from a given input source (of size K), such that the original symbols can be recovered from any subset of the encoded symbols of size equal to or slightly larger than K. However in all cases the number of source symbols recovered falls rapidly if the number of encoded symbols received falls below K. In this paper we determine the CNG code-ensembles (under statistical toplogy constraint) which result in maximal recovery of WSN source data (for different erasure-rates), thereby minimizing the deterioration in data recovery. We also perform fixed point stability analysis on the underlying LDPC code ensemble. We then propose a distributed algorithm for generating a sequence of encoded symbols adhering to the designed code ensemble. Optimal solutions for a sensor network with 1000 nodes is determined using the Differential Evolution algorithm, and the solution sensitivity to variance in number of sensor nodes and node-interconnectivity is evaluated.

Research has shown that fluid limits of Markov processes can be used to obtain closed form expressions for the evolution of the ripple-size. In this work we extend the above analysis to generalized LT (GLT) codes, which can be used to represent LT encoding (with priorities) over multiple data segments. In our analysis, we segregate the ripple into multiple colored ripples, where each color corresponds to a segment. We derive closed form expressions for the size of each ripple. We utilize these expressions to design GLT distributions, optimized for a desired intermediate and unequal recovery.

A primary focus of popular wireless link-layer protocols is to achieve some level of reliability using ARQ or Hybrid ARQ mechanisms. However, these and other leading link-layer protocols largely ignore the stability aspect of wireless communication, and rely on higher layers to provide stable traffic flow control. This design strategy has led to a great deal of inefficiency in throughput and to other major issues (such as the well-known TCP over-wireless performance degradation phenomenon and the numerous studies in attempt to fix it). In this paper, we propose a paradigm shift where both reliability and stability are targeted using an Automatic Code Embedding (ACE) wireless link-layer protocol. To the best of our knowledge this is the first effort to develop a theoretical framework for analyzing and designing a wireless link-layer protocol that targets system stability in conjunction with reliable communication. We present two distinct analytical frameworks to determine optimal code embedding rates which ensure system reliability and stability for wide range of traffic demand. An important conclusion of our analysis is that various traffic demand can be met using a packet-by-packet code embedding rate constraint that is independent of traffic type. We demonstrate experimentally that ACE provides both rapid and reliable point-to-point wireless data transmission for realtime and non-realtime traffic over real channel traces collected on 802.11b WLAN. We also have conducted extensive TCP simulations in conjunction with ACE; and we demonstrate the high level of efficiency and stability that can be achieved for TCP over ACE, while not making any changes to TCP. Further, the implementation of ACE for real-time video communication shows performance gains of 5-10dB over IEEE ARQ schemes. More importantly, ACE is layer oblivious and requires no changes to higher or lower PHY layers.

Packet drops caused byresidueerrors(MAC-layer errors) can severely deteriorate the wireless video quality. Prior studies have shown that this loss of quality can be circumvented by using forward error correction (FEC) to recover information from the corrupted packets. The performance of FEC encoded video streaming is critically dependent upon the choice of source and channel coding rates. In practice, the wireless channel conditions can vary significantly, thus altering the optimal rate choices. Thus, it is essential to develop an architecture which can estimate the channel capacity and utilize this estimate for rate allocation. In this paper we develop such a framework. Our contributions consist of two parts. In the first part we develop a prediction framework that leverages the received packets' signal to silence ratio (SSR) indications and MAC-layer checksum as side information to predict the operational channel capacity. In the second part, we use this prediction framework for rate allocation. The optimal rate allocation is dependent upon thechannelcapacity, the distribution of the (capacity)predictionerrorand the rate-distortion (RD) characteristics of the video source. Consequently, we propose a framework that utilizes the aforementioned statistics for RD optimal rate adaptation. We exhibit the efficacy of the proposed scheme by simulations using actual 802.11b wireless traces, an RD model for the video source and an ideal FEC model. Simulations using source RD models derived from five different popular video codecs (including H.264), show that the proposed framework provides up-to 5-dB improvements in peak signal-to-noise ratio (PSNR) when compared with conventional rate-adaptive schemes.

Performance of cross-layer protocols that recommend the relay of corrupted packets to higher layers can be improved significantly by accurately inferring/predicting the bit error rate (BER) in the packets. In practice, higher layers observe the bits only after some hard decision. Hence physical layer link-quality indications, such as the signal strength of each individual bit, are not observable at higher layers. Therefore, it is essential to identify practically observable variables, which can be used for reasonably robust channel state inference/prediction (CSI/CSP). Here, inference specifically refers to estimating the BER in an already received packet, while prediction refers to anticipating the BER in a future packet. In this paper, we note that, in practical 802.11b devices, it is possible to acquire a Signal to Silence Ratio (SSR) indication and measure the background traffic intensity (p) on a per packet basis. This paper, thus presents a measurement-based study that analyzes the utility of SSR andpas side-information for CSI/CSP. In this work, we exploit the method of types to measure the robustness of the observable side-information. Our analysis and simulations based on an extensive set of actual 802.11b traces exhibit the practical utility of the considered observable variables.

Retransmission based schemes are not suitable for energy constrained wireless sensor networks. Hence, there is an interest in including parity bits in each packet for error control. From an information-theoretic perspective the most efficient usage of network capacity can be achieved by performing full encoding/decoding at each node and using a variable rate in accordance with the link-quality. However, such an approach represents a major burden on power-constrained sensors. In this paper, we propose a more practical approach that is based on optimally distributing iterative channel decoding over sensor networks. In such a paradigm, the guarantee with which the base station, orcollector, gets the data from a sensor is a function of the processing within the intermediate nodes between source and destination (in-network processing). There are two extreme cases: a) Complete channel decoding at each hop and b) decoding only at the final destination. In this paper, we present a novel scheme in which intermediate nodes conduct partial decoding of LDPC coded packets. In this scheme each node is assigned some number of decoding iterations. The relay node conducts LPDC decoding for that number of iterations and forwards the packet, without ensuring a complete error correction. We show that such partial processing is sufficient to improve the end-to-end reliability significantly. Additionally, we show that it is feasible to tradeoff complexity/energy usage with distortion/reliability by varying the assignment of number of iterations. Finally, we present a low-complexity dynamic programming algorithm that optimally assigns iterations within the network to facilitate operation along an optimalenergy-distortioncurve.

Network coding (NC) can be efficiently combined with the "physical layer broadcast" property of wireless mediums to facilitate mutual exchange of independent information. At the same time, experimental/theoretical analysis of wireless networks has shown the efficacy of cross-layer protocols that relay corrupted packets in bandwidth hungry video applications. The integration of NC-based information exchange and cross-layer (CL) protocols for wireless video is the primary theme of this work. A particular issue addressed in this paper is the impact of errors in a packet, on the performance of a network code. Thus, we identify the operating conditions under which NC, despite the presence of residue errors, is beneficial. Based on theoretical analysis and experiments using 802.11b wireless traces it is established that the combination of NC with relay of corrupted packets can perform better than (i) conventional schemes that drop all corrupted packets (ii) a scheme that deploys network coding only (iii) a scheme that only deploys a CL strategy that recovers information from corrupted packets. The proposed cross-layer exchange (CLIX) scheme significantly improves the performance of an H.264 based video codec for wireless networks.

Radio hardware used for the reception of 802.11b frames is capable of associating a signal to silence ratio (SSR) with each received frame. If a received frame is corrupted, then these SSR indications can be used to provide robust apriori estimate of the bit error rate in the packet. In many recently proposed cross-layer protocols, for transmission of video over wireless networks, recovery of information from partially corrupted packets has shown significant utility. In this paper, based on experiments with actual 802.11b error traces, we show that the channel state information (CSI) provided by the SSR indications can be used to improve the error recovery performance of an FEC scheme employed in conjunction with a cross-layer protocol. H.264 based simulation are used to establish the efficacy of the proposed work for video applications; specifically for video over 802.11b WLAN