Bits-per-Joule Capacity of Energy-Limited Wireless Networks

For a wireless network in which every node is bounded in its energy supply, we define a new concept of network capacity called "bits-per-Joule capacity", which is the maximum total number of bits that the network can deliver per Joule of energy deployed into the network. For a fixed network size, a finite number of information bits is delivered for each source-destination pair, under a fixed end-to-end probability of error constraint. We prove that under the one-to-one traffic model in which every node wants to send traffic to a randomly chosen destination node, the bits-per-Joule capacity of a stationary wireless network grows asymptotically as Omega((N/logN)^(q-1)/2 ), where N is the number of nodes randomly deployed onto the surface of a sphere and q is the path loss exponent. Further, the length of the block codes used grows only logarithmically in N, which indicates manageable decoder complexity as the network scales. The fact that the bits-per-Joule capacity grows with the number of nodes contrasts sharply with the scaling laws that have been derived for throughput capacity and implies that large-scale deployments for energy-limited sensor and ad hoc networks may be suitable for delay-tolerant data applications     

Core Capacity Region of Portable Wireless Networks

We analyze the core capacity region of portable wireless networks under a concave utility model for a heterogeneous collection of asynchronous applications such as email and file transfers. We prove that the core capacity region is non-empty under the concave utility model. We show that there is no relaying among portable users in the core capacity region under the many-to-one traffic model for a single type of traffic. However, heterogeneous traffic induces cooperation when the channel conditions are matched to the type of traffic delivered. We demonstrate that each node can increase its utility by allocating its energy across different portable network configurations. The results motivate the use of energy-limited relays in next-generation wireless LAN systems.     

Energy Maps for Mobile Wireless Networks: Coherence Time versus Spreading Period

We show that even though mobile networks are highly unpredictable when viewed at the individual node scale, the end-to-end quality-of-service (QoS) metrics can be stationary when the mobile network is viewed in the aggregate. We define the coherence time as the maximum duration for which the end-to-end QoS metric remains roughly constant, and the spreading period as the minimum duration required to spread QoS information to all the nodes. We show that if the coherence time is greater than the spreading period, the end-to-end QoS metric can be tracked. We focus on the energy consumption as the end-to-end QoS metric, and describe a novel method by which an energy map can be constructed and refined in the joint memory of the mobile nodes. Finally, we show how energy maps can be utilized by an application that aims to minimize a node's total energy consumption over its near-future trajectory.     

Algorithms for the MIMO Single Relay Channel

The MIMO single relay channel consists of a transmitter, a relay, and a receiver, all equipped with multiple antennas, located in an environment with distance-dependent path loss as well as scattering. We describe an optimal and a heuristic algorithm to solve the spatial energy allocation problem for the MIMO single relay channel when the scattering clusters on the direct and relay links are non-overlapping. These algorithms can be applied to existing wireless LAN systems that aim to increase their performance via relays. By simulations, we compare the performances of joint and uniform energy allocations across the spatial channels, and the performances of a direct transmission system and a system that utilizes the relay node     

Minimum energy mobile wireless networks

We describe a distributed position-based network protocol optimized for minimum energy consumption in mobile wireless networks that support peer-to-peer communications. Given any number of randomly deployed nodes over an area, we illustrate that a simple local optimization scheme executed at each node guarantees strong connectivity of the entire network and attains the global minimum energy solution for stationary networks. Due to its localized nature, this protocol proves to be self-reconfiguring and stays close to the minimum energy solution when applied to mobile networks. Simulation results are used to verify the performance of the protocol