Shirin Saeedi Bidokhti

Non-Cooperative Multi-Radio Channel Allocation in Wireless Networks

Channel allocation was extensively studied in the framework of cellular networks. But the emergence of new system concepts, such as cognitive radio systems, has brought this topic into the focus of research again. In this paper, we study in detail the problem of competitive multi-radio multi-channel allocation in wireless networks. We study the existence of Nash equilibria in a static game and we conclude that, in spite of the non-cooperative behavior of such devices, their channel allocation results in a load-balancing solution. In addition, we consider the fairness properties of the resulting channel allocations and their resistance to the possible coalitions of a subset of players. Finally, we present three algorithms that achieve a load-balancing Nash equilibrium channel allocation; each of them using a different set of available information.

Erasure broadcast networks with receiver caching

We study the capacity of a broadcast packet-erasure network with receiver caching. The receivers in the network are divided into two groups: A group of strong receivers with small packet erasure probabilities, and a group of weak receivers with large packet erasure probabilities. The weak receivers are provided with local cache memories as compensation for their poor channels. Achievable (lower) and converse (upper) bounds for the optimal capacity-memory tradeoff are derived. The lower bounds are proved using new joint cache-channel coding schemes that significantly outperform naive separate cache-channel coding schemes. For the case of two receivers, the capacity-memory tradeoff is completely characterized for a range of useful cache memory sizes.

Is Non-Unique Decoding Necessary?

In multiterminal communication systems, signals carrying messages meant for different destinations are often observed together at any given destination receiver. Han and Kobayashi proposed a receiving strategy, which performs a joint unique decoding of messages of interest along with a subset of messages, which are not of interest. It is now well-known that this provides an achievable region, which is, in general, larger than if the receiver treats all messages not of interest as noise. Nair and El Gamal and Chong, Motani, Garg, and El Gamal independently proposed a generalization called indirect or nonunique decoding where the receiver uses the codebook structure of the messages to uniquely decode only its messages of interest. Nonunique decoding has since been used in various scenarios. The main result in this paper is to provide an interpretation and a systematic proof technique for why nonunique decoding, in all known cases where it has been employed, can be replaced by a particularly designed joint unique decoding strategy, without any penalty from a rate region viewpoint.

An upper bound on the capacity-memory tradeoff of degraded broadcast channels

We present a general upper bound on the capacity-memory tradeoff over degraded broadcast channels (BCs) with cache memories at the receivers.

Capacity Bounds for Diamond Networks With an Orthogonal Broadcast Channel

A class of diamond networks is studied where the broadcast component is orthogonal and modeled by two independent bit-pipes. New upper and lower bounds on the capacity are derived. The proof technique for the upper bound generalizes the bounding techniques of Ozarow for the Gaussian multiple description problem (1981) and Kang and Liu for the Gaussian diamond network (2011). The lower bound is based on Martons coding technique and superposition coding. The bounds are evaluated for Gaussian and binary adder multiple access channels (MACs). For Gaussian MACs, both the lower and upper bounds strengthen the Kang-Liu bounds and establish capacity for interesting ranges of bit-pipe capacities. For binary adder MACs, the capacity is established for all the ranges of bit-pipe capacities.

Capacity bounds for a class of diamond networks

A class of diamond networks is studied where the broadcast component is modelled by two independent bit-pipes. New upper and lower bounds are derived on the capacity which improve previous bounds. The upper bound is in the form of a max-min problem, where the maximization is over a coding distribution and the minimization is over an auxiliary channel. The proof technique generalizes bounding techniques of Ozarow for the Gaussian multiple description problem (1981) and Kang and Liu for the Gaussian diamond network (2011). The bounds are evaluated for a Gaussian multiple access channel (MAC) and the binary adder MAC, and the capacity is found for interesting ranges of the bit-pipe capacities.

Feedback-based coding algorithms for broadcast erasure channels with degraded message sets

We consider single-hop broadcast packet erasure channels (BPEC) with degraded message sets and instantaneous feedback regularly available from all receivers, and demonstrate that the main principles of the virtual-queue-based algorithms in [1], which were proposed for multiple unicast sessions, can still be applied to this setting and lead to capacity-achieving algorithms. Specifically, we propose a generic class of algorithms and intuitively describe its rationale and properties that result in its efficiency. We then apply this class of algorithms to three examples of BPEC channels (with different numbers of users and 2 or 3 degraded message sets) and show that the achievable throughput region matches a known capacity outer bound, assuming feedback availability through a separate public channel. If the feedback channel is not public, all users can still decode their messages, albeit at some overhead which results in an achievable throughput that differs from the outer bound by O(N/L), where L is the packet length. These algorithms do not require any prior knowledge of channel statistics for their operation.

Degraded Multicasting with Network Coding over the Combination Network

In this paper, we give a characterization of the rate region for the degraded two message set problem, applied to a combination network with erasure channels. We also provide an algorithm that uses topological information in order to deliver the two messages to the receivers, and we show that our algorithm is optimal, in the sense that it achieves any rate pair in the region. We compare our algorithm analytically with a naive approach oblivious to the network structure, and we give an insight on what benefits should be expected for different classes of networks.

Is non-unique decoding necessary?

In multiterminal communication systems, signals carrying messages meant for different destinations are often observed together at any given destination receiver. Han and Kobayashi proposed a receiving strategy, which performs a joint unique decoding of messages of interest along with a subset of messages, which are not of interest. It is now well-known that this provides an achievable region, which is, in general, larger than if the receiver treats all messages not of interest as noise. Nair and El Gamal and Chong, Motani, Garg, and El Gamal independently proposed a generalization called indirect or nonunique decoding where the receiver uses the codebook structure of the messages to uniquely decode only its messages of interest. Nonunique decoding has since been used in various scenarios. The main result in this paper is to provide an interpretation and a systematic proof technique for why nonunique decoding, in all known cases where it has been employed, can be replaced by a particularly designed joint unique decoding strategy, without any penalty from a rate region viewpoint.

Gaussian broadcast channels with receiver cache assignment

This paper considers a K-user Gaussian broadcast channel (BC) where receivers are equipped with cache memories. Lower and upper bounds are established on the capacity-memory tradeoff, i.e., the largest rate achievable for given cache-memories. The lower bound is based on a joint cache-channel coding scheme which generalizes the recently proposed piggyback coding to Gaussian BCs with unequal cache sizes. This paper also establishes lower and upper bounds on the global capacity-memory tradeoff, i.e., the maximum capacity-memory tradeoff over all possible cache assignments subject to a total cache memory constraint. The bounds match when the total cache memory is sufficiently large. It is shown that significantly larger rates can be achieved by carefully assigning larger cache memories to weaker receivers. In particular, cache allocation allows communication at rates that are (fundamentally) impossible to achieve with equal cache assignment. This shows the merit in carefully designing the cache size allocation in conjunction with channel qualities.