Instantly Decodable Network Coding: From Point to Multi-Point to Device-to-Device Communications

Abstract

The network coding paradigm enhances transmission efficiency by combining information flows and has drawn significant attention in information theory, networking, communications and data storage. Instantly decodable network coding (IDNC), a subclass of network coding, has demonstrated its ability to improve the quality of service of time critical applications thanks to its attractive properties, namely the throughput enhancement, delay reduction, simple XOR-based encoding and decoding, and small coefficient overhead. Nonetheless, for point to multi-point (PMP) networks, IDNC cannot guarantee the decoding of a specific new packet at individual devices in each transmission. Furthermore, for device-to-device (D2D) networks, the transmitting devices may possess only a subset of packets, which can be used to form coded packets. These challenges require the optimization of IDNC algorithms to be suitable for different application requirements and network configurations.

In this thesis, we first study a scalable live video broadcast over a wireless PMP network, where the devices receive video packets from a base station. Such layered live video has a hard deadline and imposes a decoding order on the video layers. We design two prioritized IDNC algorithms that provide a high level of priority to the most important video layer before considering additional video layers in coding decisions. These prioritized algorithms are shown to increase the number of decoded video layers at the devices compared to the existing network coding schemes.

We then study video distribution over a partially connected D2D network, where a group of devices cooperate with each other to recover their missing video content. We introduce a cooperation aware IDNC graph that defines all feasible coding and transmission conflictfree decisions. Using this graph, we propose an IDNC solution that avoids coding and transmission conflicts, and meets the hard deadline for high importance video packets. It is demonstrated that the proposed solution delivers an improved video quality to the devices compared to the video and cooperation oblivious coding schemes.

We also consider a heterogeneous network wherein devices use two wireless interfaces to receive packets from the base station and another device concurrently. For such network, we are interested in applications with reliable in-order packet delivery requirements. We represent all feasible coding opportunities and conflict-free transmissions using a dual interface IDNC graph. We select a maximal independent set over the graph by considering dual interfaces of individual devices, in-order delivery requirements of packets and lossy channel conditions. This graph based solution is shown to reduce the in-order delivery delay compared to the existing network coding schemes.

Finally, we consider a D2D network with a group of devices experiencing heterogeneous channel capacities. For such cooperative scenarios, we address the problem of minimizing the completion time required for recovering all missing packets at the devices using IDNC and physical layer rate adaptation. Our proposed IDNC algorithm balances between the adopted transmission rate and the number of targeted devices that can successfully receive the transmitted packet. We show that the proposed rate aware IDNC algorithm reduces the completion time compared to the rate oblivious coding schemes