Pliable Index Coding | EPFL Graph Search

We formulate a new variant of the index coding problem, where instead of demanding a specific message, clients are pliable, and are interested in receiving any t messages that they do not have. We term this problem pliable index coding or PICOD(t). We prove that, with this formulation, although some instances of the problem become simple, in general, the problem of finding the optimal linear code remains NP-hard. However, we show that it is possible to construct pliable index codes that are substantially smaller than index codes in many cases. If there are n clients, the server has m messages, and each client has a side information set of cardinality s > log(2) n, the number of broadcast transmissions required is only linearly dependent on t. We generalize the results to instances where the side information sets are not necessarily of equal cardinality. When m = O(n(delta)), for some constant delta > 0, we show that the codes of size O(min{t log(2) n, t log n + log(3) n}) are sufficient in general. We also consider the scenario when the server only knows the cardinality of the side information sets of the clients and each client is interested in receiving any t messages that it does not have. We term this formulation oblivious pliable index coding or OB-PICOD(t). If the cardinalities of side information sets of all the clients is s (with s

Pliable Index Coding

Siddhartha Brahma, Christina Fragouli

We propose a new formulation of the index coding problem, where instead of demanding a specific message, clients are “pliable” and are happy to receive any one message they do not have. We prove that with this relaxation, although some instances of this problem become simple, in general the problem remains NP-hard. However, we develop heuristic algorithms that in our (extensive) experimental evaluation required only a logarithmic (in the number of messages) number of broadcast transmissions; this is an exponential improvement over tradi- tional index coding requirements.

Ieee2012

Low Complexity Scheduling and Coding for Wireless Networks

Siddhartha Brahma

The advent of wireless communication technologies has created a paradigm shift in the accessibility of communication. With it has come an increased demand for throughput, a trend that is likely to increase further in the future. A key aspect of these challenges is to develop low complexity algorithms and architectures that can take advantage of the nature of the wireless medium like broadcasting and physical layer cooperation. In this thesis, we consider several problems in the domain of low complexity coding, relaying and scheduling for wireless networks. We formulate the Pliable Index Coding problem that models a server trying to send one or more new messages over a noiseless broadcast channel to a set of clients that already have a subset of messages as side information. We show through theoretical bounds and algorithms, that it is possible to design short length codes, poly-logarithmic in the number of clients, to solve this problem. The length of the codes are exponentially better than those possible in a traditional index coding setup. Next, we consider several aspects of low complexity relaying in half-duplex diamond networks. In such networks, the source transmits information to the destination through

n

half-duplex intermediate relays arranged in a single layer. The half-duplex nature of the relays implies that they can either be in a listening or transmitting state at any point of time. To achieve high rates, there is an additional complexity of optimizing the schedule (i.e. the relative time fractions) of the relaying states, which can be

2^n

in number. Using approximate capacity expressions derived from the quantize-map-forward scheme for physical layer cooperation, we show that for networks with

n\leq 6

relays, the optimal schedule has atmost

n+1

active states. This is an exponential improvement over the possible

2^n

active states in a schedule. We also show that it is possible to achieve at least half the capacity of such networks (approximately) by employing simple routing strategies that use only two relays and two scheduling states. These results imply that the complexity of relaying in half-duplex diamond networks can be significantly reduced by using fewer scheduling states or fewer relays without adversely affecting throughput. Both these results assume centralized processing of the channel state information of all the relays. We take the first steps in analyzing the performance of relaying schemes where each relay switches between listening and transmitting states randomly and optimizes their relative fractions using only local channel state information. We show that even with such simple scheduling, we can achieve a significant fraction of the capacity of the network. Next, we look at the dual problem of selecting the subset of relays of a given size that has the highest capacity for a general layered full-duplex relay network. We formulate this as an optimization problem and derive efficient approximation algorithms to solve them. We end the thesis with the design and implementation of a practical relaying scheme called QUILT. In it the relay opportunistically decodes or quantizes its received signal and transmits the resulting sequence in cooperation with the source. To keep the complexity of the system low, we use LDPC codes at the source, interleaving at the relays and belief propagation decoding at the destination. We evaluate our system through testbed experiments over WiFi.

EPFL2015