Kiran Misra

An Overview of Tiles in HEVC

Tiles is a new feature in the High Efficiency Video Coding (HEVC) standard that divides a picture into independent, rectangular regions. This division provides a number of advantages. Specifically, it increases the “parallel friendliness” of the new standard by enabling improved coding efficiency for parallel architectures, as compared to previous sliced based methods. Additionally, tiles facilitate improved maximum transmission unit (MTU) size matching, reduced line buffer memory, and additional region-of-interest functionality. In this paper, we introduce the tiles feature and survey the performance of the tool. Coding efficiency is reported for different parallelization factors and MTU size requirements. Additionally, a tile-based region of interest coding method is developed.

Delay Constraint Error Control Protocol for Real-Time Video Communication

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.

Natural growth codes: Partial recovery under random network coding

Growth codes (GC) improve the disruption tolerance of zero-configuration sensor networks by providing graceful data recovery. Here, we highlight the existence of periphery monitoring topologies which are conducive for graceful recovery. In such networks, the performance of random network coding (RNC) is observed to be superior to that of GCs. RNC increases the data persistence, while maintaining a lower delay.

On link-layer reliability and stability for wireless communication

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.

McFIS in hierarchical bipredictve pictures-based video coding for referencing the stable area in a scene

In this paper, we outline a coding strategy that initializes the entropy coding engine of a video codec at pre-defined locations within a bit-stream. Coupled with the causal dependencies of state-of-the-art video coding systems, this enables wavefront processing of the entropy decoding and reconstruction process simultaneously. Approaches to wavefront processing have been considered by others, and those methods either address the reconstruction process solely or require transmitting image data in non-raster scan order. Here, our key contribution is that we enable simultaneous entropy/reconstruction wavefront processing while still preserving a raster scan strategy. In this paper, we describe the system, as well as different strategies for initializing the context models. The performance of the proposed methods is evaluated, and the bitrate increase is shown to be nominal.In this paper, we outline a coding strategy that initializes the entropy coding engine of a video codec at pre-defined locations within a bit-stream. Coupled with the causal dependencies of state-of-the-art video coding systems, this enables wavefront processing of the entropy decoding and reconstruction process simultaneously. Approaches to wavefront processing have been considered by others, and those methods either address the reconstruction process solely or require transmitting image data in non-raster scan order. Here, our key contribution is that we enable simultaneous entropy/reconstruction wavefront processing while still preserving a raster scan strategy. In this paper, we describe the system, as well as different strategies for initializing the context models. The performance of the proposed methods is evaluated, and the bitrate increase is shown to be nominal.

On Channel Capacity Estimation and Prediction for Rate-Adaptive Wireless Video

Packet drops caused by residue errors (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 the channel capacity, the distribution of the (capacity) prediction error and 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.

Tiles for managing computational complexity of video encoding and decoding

In this paper, we introduce the concept of tiles. Tiles are incorporated into the current design of the High Efficiency Video Coding (HEVC) standard being developed by the Joint Collaborative Team on Video Coding (JCT-VC). In the design, tiles are introduced to support high-level parallelism and also to reduce on-chip memory requirements. This paper describes the tile concept and reports results due to the technique.

Design and analysis of Generalized LT-codes using colored ripples

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.

Optimally Mapping an Iterative Channel Decoding Algorithm to a Wireless Sensor Network

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, or collector, 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 optimal energy-distortion curve.

On Channel State Inference and Prediction Using Observable Variables in 802.11b Network

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 and p as 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.