Edmund M. Yeh

Throughput Optimal Control of Cooperative Relay Networks

In cooperative relaying, multiple nodes cooperate to forward a packet within a network. To date, such schemes have been primarily investigated at the physical layer with the focus on communication of a single end-to-end flow. This paper considers cooperative relay networks with multiple stochastically varying flows, which may be queued within the network. Throughput optimal network control policies are studied that take into account queue dynamics to jointly optimize routing, scheduling and resource allocation. To this end, a generalization of the maximum differential backlog algorithm is given, which takes into account the cooperative gains in the network. Several structural characteristics of this policy are discussed for the special case of parallel relay networks.

Polar Codes for the Two-User Multiple-Access Channel

Arikans polar coding method is extended to two-user multiple-access channels. It is shown that if the two users of the channel use Arikans construction, the resulting channels will polarize to one of five possible extremals, on each of which uncoded transmission is optimal. The sum rate achieved by this coding technique is the one that corresponds to uniform input distributions. The encoding and decoding complexities and the error performance of these codes are as in the single-user case: O(nlogn) for encoding and decoding, and o(2-n1/2-ε) for the block error probability, where n is the blocklength.

On the latency for information dissemination in mobile wireless networks

In wireless networks, node mobility may be exploited to assist in information dissemination over time. We analyze the latency for information dissemination in large-scale mobile wireless networks. To study this problem, we map a network of mobile nodes to a network of stationary nodes with dynamic links. We then use results from percolation theory to show that under a constrained i.i.d. mobility model, the scaling behavior of the latency falls into two regimes. When the network is not percolated (subcritical), the latency scales linearly with the initial Euclidean distance between the sender and the receiver; when the network is percolated (supercritical), the latency scales sub-linearly with the distance.

Distributed algorithms for minimum cost multicast with network coding

Network coding techniques are used to find the minimum-cost transmission scheme for multicast sessions with or without elastic rate demand. It is shown that in wireline networks, solving for the optimal coding subgraphs in network coding is equivalent to finding the optimal routing scheme in a multicommodity flow problem. A set of node-based distributed gradient projection algorithms are designed to jointly implement congestion control/routing at the source node and ¿virtual¿ routing at intermediate nodes. The analytical framework and distributed algorithms are further extended to interference-limited wireless networks where link capacities are functions of the signal-to-interference-plus-noise ratio (SINR). To achieve minimum-cost multicast in this setting, the transmission powers of links must be jointly optimized with coding subgraphs and multicast input rates. Node-based power allocation and power control algorithms are developed for the power optimization. The power algorithms, when iterated in conjunction with the congestion control and routing algorithms, converge to the jointly optimal multicast configuration. The scaling matrices required in the gradient projection algorithms are explicitly derived and are shown to guarantee fast convergence to the optimum from any initial condition.

Connectivity and Latency in Large-Scale Wireless Networks with Unreliable Links

We study connectivity and transmission latency in wireless networks with unreliable links from a percolation-based perspective. We first examine static models, where each link of the network is functional (active) with some probability, independently of all other links, where the probability may depend on the distance between the two nodes. We obtain analytical upper and lower bounds on the critical density for phase transition in this model. We then examine dynamic models, where each link is active or inactive according to a Markov on- off process. We show that a phase transition also exists in such dynamic networks, and the critical density for this model is the same as the one for static networks under some mild conditions. Furthermore, due to the dynamic behavior of links, a delay is incurred for any transmission even when propagation delay is ignored. We study the behavior of this transmission delay and show that the delay scales linearly with the Euclidean distance between the sender and the receiver when the network is in the subcritical phase, and the delay scales sub-linearly with the distance if the network is in the supercritical phase.

Distributed energy management algorithm for large-scale wireless sensor networks

In battery-constrained wireless sensor networks, it is important to employ effective energy management while maintaining some level of network connectivity. Viewing this problem from a percolation-based connectivity perspective, we propose a fully distributed energy management algorithm for large-scale wireless sensor networks. This algorithm allows each sensor to probabilistically schedule its own activity based on its node degree. This mechanism is modelled by a degree-dependent dynamic site percolation process on random geometric graphs. We specify the conditions under which the resulting network is guaranteed to be percolated at all the time. We further study the delay performance of the proposed energy management algorithm by modelling the problem as a degree-dependent first passage percolation process on random geometric graphs.

Distributed algorithms for spectrum allocation, power control, routing, and congestion control in wireless networks

We develop distributed algorithms to allocate resources in multi-hop wireless networks with the aim of minimizing the total cost. In order to observe the fundamental duplexing constraint that co-located transmitters and receivers cannot operate simultaneously on the same frequency band, we first devise a spectrum allocation scheme that divides the whole spectrum into multiple sub-bands and activates conflict-free links on each sub-band. We show that the minimum number of required sub-bands grows asymptotically at a logarithmic rate with the chromatic number of network connectivity graph. A simple distributed and asynchronous algorithm is developed to feasibly activate links on the available sub-bands. Given a feasible spectrum allocation, we then develop node-based distributed algorithms for optimally controlling the transmission powers on active links for each sub-band, jointly with traffic routes and user input rates in response to channel states and traffic demands. We show that under specified conditioans, the algorithms asymptotically converge to the optimal operating point.

VIP: a framework for joint dynamic forwarding and caching in named data networks

Emerging information-centric networking architectures seek to optimally utilize both bandwidth and storage for efficient content distribution. This highlights the need for joint design of traffic engineering and caching strategies, in order to optimize network performance in view of both current traffic loads and future traffic demands. We present a systematic framework for joint dynamic interest request forwarding and dynamic cache placement and eviction, within the context of the Named Data Networking (NDN) architecture. The framework employs a virtual control plane which operates on the user demand rate for data objects in the network, and an actual plane which handles Interest Packets and Data Packets. We develop distributed algorithms within the virtual plane to achieve network load balancing through dynamic forwarding and caching, thereby maximiz- ing the user demand rate that the NDN network can satisfy. Numerical experiments within a number of network settings demonstrate the superior performance of the resulting algorithms for the actual plane in terms of low user delay and high rate of cache hits.

Throughput optimal control of cooperative relay networks

We give a model for cooperative communication in a parallel relay network that includes the stochastic arrival of packets and queueing. Exogenous arrivals at both the non-relay and the relay nodes are allowed. For this model, we provide a throughput optimal network control policy which stabilizes the network for any vector of arrival rates in its stability region. This policy generalizes the maximum differential backlog policies, taking into account potential cooperative gains in the network. Some structural properties of this policy are also discussed

Throughput optimal power and rate control for queued multiaccess and broadcast communications

An adaptive joint power control/rate allocation policies which maximize system throughput for multiaccess and broadcast fading channels with random packet arrivals and queueing is established in this paper.