Content Delivery in Erasure Broadcast Channels with Cache and Feedback

We study a content delivery problem in a K-user erasure broadcast channel such that a content providing server wishes to deliver requested files to users, each equipped with a cache of a finite memory. Assuming that the transmitter has state feedback and user caches can be filled during off-peak hours reliably by the decentralized content placement, we characterize the achievable rate region as a function of the memory sizes and the erasure probabilities. The proposed delivery scheme, based on the broadcasting scheme by Wang and Gatzianas et al., exploits the receiver side information established during the placement phase. Our results can be extended to centralized content placement as well as multi-antenna broadcast channels with state feedback.Comment: 29 pages, 7 figures. A short version has been submitted to ISIT 201

Instantly Decodable Network Coding: From Centralized to Device-to-Device Communications

From its introduction to its quindecennial, network coding has built a strong reputation for enhancing packet recovery and achieving maximum information flow in both wired and wireless networks. Traditional studies focused on optimizing the throughput of the system by proposing elaborate schemes able to reach the network capacity. With the shift toward distributed computing on mobile devices, performance and complexity become both critical factors that affect the efficiency of a coding strategy. Instantly decodable network coding presents itself as a new paradigm in network coding that trades off these two aspects. This paper review instantly decodable network coding schemes by identifying, categorizing, and evaluating various algorithms proposed in the literature. The first part of the manuscript investigates the conventional centralized systems, in which all decisions are carried out by a central unit, e.g., a base-station. In particular, two successful approaches known as the strict and generalized instantly decodable network are compared in terms of reliability, performance, complexity, and packet selection methodology. The second part considers the use of instantly decodable codes in a device-to-device communication network, in which devices speed up the recovery of the missing packets by exchanging network coded packets. Although the performance improvements are directly proportional to the computational complexity increases, numerous successful schemes from both the performance and complexity viewpoints are identified

Local network coding on packet erasure channels -- From Shannon capacity to stability region

Network Coding (NC) has emerged as a ubiquitous technique of communication networks and has extensive applications in both practical implementations and theoretical developments. While the Avalanche P2P file system from Microsoft, the MORE routing protocol, and the COPE coding architecture from MIT have implemented the idea of NC and exhibited promising performance improvements, a significant part of the success of NC stems from the continuing theoretic development of NC capacity, e.g., the Shannon capacity results for the single-flow multi-cast network and the packet erasure broadcast channel with feedback. However, characterizing the capacity for the practical wireless multi-flow network setting remains a challenging topic in NC. For example, the difficulties of finding the optimal NC strategy over multiple flows under varying-channel qualities and the rate adaption scenarios hinder any further advancement in this area. Despite the difficulty of characterizing the full capacity for large networks, there are evidences showing that even when using only local operations, NC can still recover substantial NC gain. We believe that a deeper understanding of multi-flow local network coding will play a key role in designing the next-generation high-throughput coding-based wireless network architecture. This thesis consists of three parts. In the first part, we characterize the full Shannon capacity region of the COPE principle when applied to a 2-flow wireless butterfly network with broadcast packet erasure channels. The capacity results allow for random overhearing probabilities, arbitrary scheduling policies, network-wide channel state information (CSI) feedback after each transmission, and potential use of non-linear network codes. We propose a theoretical outer bound and a new class of linear network codes, named the Space-Based Linear Network Coding (SBLNC), that achieves the capacity outer bound. Numerical experiments show that SBLNC provides close-to-optimal throughput even in the scenario with opportunistic routing. In the second part, we further consider the complete network dynamics of stochastic arrivals and queueing and study the corresponding stability region. Based on dynamic packet arrivals, the resulting solution would be one step closer to practical implementation, when compared to the previous block-code-based capacity study. For the 2-flow downlink scenario, we propose the first opportunistic INC + scheduling solution that is provably optimal for time-varying channels, i.e., the corresponding stability region matches the optimal Shannon capacity. Specifically, we first introduce a new binary INC operation, which is distinctly different from the traditional wisdom of XORing two overheard packets. We then develop a queue-length-based scheduling scheme, which, with the help of the new INC operation, can robustly and optimally adapt to time-varying channel quality. We then show that the proposed algorithm can be easily extended for rate adaptation and it again robustly achieves the optimal throughput. In the third part, we propose an 802.11-based MAC layer protocol which incorporates the rate adaption solution developed in the second part. The new MAC protocol realizes the promised intersession network coding gain for two-flow downlink traffic with short decoding delay. Furthermore, we delicately retain the CSMA-CA distributed contention mechanism with only 17 bits new header field changes, and carefully ensure the backward compatibility. In summary, the new solution demonstrates concrete throughput improvement without alternating the too much packet-by-packet traffic behavior. Such a feature is critical in practical implementation since it allows the network coding solution to be transparent to any arbitrary upper layer applications

Robust And Optimal Opportunistic Scheduling For Downlink 2-Flow Network Coding With Varying Channel Quality and Rate Adaptation

This paper considers the downlink traffic from a base station to two different clients. When assuming infinite backlog, it is known that inter-session network coding (INC) can significantly increase the throughput of each flow. However, the corresponding scheduling solution (when assuming dynamic arrivals instead and requiring bounded delay) is still nascent. For the 2-flow downlink scenario, we propose the first opportunistic INC + scheduling solution that is provably optimal for time-varying channels, i.e., the corresponding stability region matches the optimal Shannon capacity. Specifically, we first introduce a new binary INC operation, which is distinctly different from the traditional wisdom of XORing two overheard packets. We then develop a queue-length-based scheduling scheme, which, with the help of the new INC operation, can robustly and optimally adapt to time-varying channel quality. We then show that the proposed algorithm can be easily extended for rate adaptation and it again robustly achieves the optimal throughput. A byproduct of our results is a scheduling scheme for stochastic processing networks (SPNs) with random departure, which relaxes the assumption of deterministic departure in the existing results. The new SPN scheduler could thus further broaden the applications of SPN scheduling to other real-world scenarios

Queue stability analysis in network coded wireless multicast.

In this dissertation queue stability in wireless multicast networks with packet erasure channels is studied. Our focus is on optimizing packet scheduling so as to maximize throughput. Specifically, new queuing strategies consisting of several sub-queues are introduced, where all newly arrived packets are first stored in the main sub-queue on a first-come-first-served basis. Using the receiver feedback, the transmitter combines packets from different sub-queues for transmission. Our objective is to maximize the input rate under the queue stability constraints. Two packet scheduling and encoding algorithms have been developed. First, the optimization problem is formulated as a linear programming (LP) problem, according to which a network coding based optimal packet scheduling scheme is obtained. Second, the Lyapunov optimization model is adopted and decision variables are defined to derive a network coding based packet scheduling algorithm, which has significantly less complexity and smaller queue backlog compared with the LP solution. Further, an extension of the proposed algorithm is derived to meet the requirements of time-critical data transmission, where each packet expires after a predefined deadline and then dropped from the system. To minimize the average transmission power, we further derive a scheduling policy that simultaneously minimizes both power and queue size, where the transmitter may choose to be idle to save energy consumption. Moreover, a redundancy in the schedules is inadvertently revealed by the algorithm. By detecting and removing the redundancy we further reduce the system complexity. Finally, the simulation results verify the effectiveness of our proposed algorithms over existing works