The Generalized Degrees of Freedom of the Interference Relay Channel with Strong Interference

The interference relay channel (IRC) under strong interference is considered. A high-signal-to-noise ratio (SNR) generalized degrees of freedom (GDoF) characterization of the capacity is obtained. To this end, a new GDoF upper bound is derived based on a genie-aided approach. The achievability of the GDoF is based on cooperative interference neutralization. It turns out that the relay increases the GDoF even if the relay-destination link is weak. Moreover, in contrast to the standard interference channel, the GDoF is not a monotonically increasing function of the interference strength in the strong interference regime.Comment: 8 pages, 4 figures, Allerton 201

Approximate Capacity of a Class of Gaussian Interference-Relay Networks

In this paper, we study a Gaussian relay-interference network, in which relay (helper) nodes are to facilitate competing information flows between different source-destination pairs. We focus on two-stage relay-interference networks where there are weak cross links, causing the networks to behave like a chain of Z Gaussian channels. Our main result is an approximate characterization of the capacity region for such ZZ and ZS networks. We propose a new interference management scheme, termed interference neutralization, which is implemented using structured lattice codes. This scheme allows for over-the-air interference removal, without the transmitters having complete access the interfering signals. This scheme in conjunction a new network decomposition technique provides the approximate characterization. Our analysis of these Gaussian networks is based on insights gained from an exact characterization of the corresponding linear deterministic model

Computation Alignment: Capacity Approximation without Noise Accumulation

Consider several source nodes communicating across a wireless network to a destination node with the help of several layers of relay nodes. Recent work by Avestimehr et al. has approximated the capacity of this network up to an additive gap. The communication scheme achieving this capacity approximation is based on compress-and-forward, resulting in noise accumulation as the messages traverse the network. As a consequence, the approximation gap increases linearly with the network depth. This paper develops a computation alignment strategy that can approach the capacity of a class of layered, time-varying wireless relay networks up to an approximation gap that is independent of the network depth. This strategy is based on the compute-and-forward framework, which enables relays to decode deterministic functions of the transmitted messages. Alone, compute-and-forward is insufficient to approach the capacity as it incurs a penalty for approximating the wireless channel with complex-valued coefficients by a channel with integer coefficients. Here, this penalty is circumvented by carefully matching channel realizations across time slots to create integer-valued effective channels that are well-suited to compute-and-forward. Unlike prior constant gap results, the approximation gap obtained in this paper also depends closely on the fading statistics, which are assumed to be i.i.d. Rayleigh.Comment: 36 pages, to appear in IEEE Transactions on Information Theor

Measuring Inter-DNA Potentials in Solution

Interactions between short strands of DNA can be tuned from repulsive to attractive by varying solution conditions and have been quantified using small angle x-ray scattering techniques. The effective DNA interaction charge was extracted by fitting the scattering profiles with the generalized one-component method and inter-DNA Yukawa pair potentials. A significant charge is measured at low to moderate monovalent counterion concentrations, resulting in strong inter-DNA repulsion. The charge and repulsion diminish rapidly upon the addition of divalent counterions. An intriguing short range attraction is observed at surprisingly low divalent cation concentrations, ~16 mM Mg2+. Quantitative measurements of inter- DNA potentials are essential for improving models of fundamental interactions in biological systems