Random Extended Networks Research Articles

Wireless Backhaul Networks: Capacity Bound, Scalability Analysis and Design Guidelines

This paper studies the scalability of a wireless backhaul network modeled as a random extended network with multiantenna base stations (BSs), where the number of antennas per BS is allowed to scale as a function of the network size. The antenna scaling is justified by the current trend toward the use of higher carrier frequencies, which allows packing a large number of antennas in small form factors. The main goal is to study the per-BS antenna requirement that ensures scalability of this network, i.e., its ability to deliver nonvanishing rate to each source–destination pair. We first derive an information theoretic upper bound on the capacity of this network under a general propagation model, which provides a lower bound on the per-BS antenna requirement. Then, we characterize the scalability requirements for two competing strategies of interest: 1) long hop : each source–destination pair minimizes the number of hops by sacrificing multiplexing gain while achieving full beamforming (power) gain over each hop; and 2) short hop : each source–destination pair communicates through a series of short hops, each achieving full multiplexing gain. While long hop may seem more intuitive in the context of massive multiple-input–multiple-output transmission, we show that the short hop strategy is significantly more efficient in terms of per-BS antenna requirement for throughput scalability. As a part of the proof, we construct a scalable short hop strategy and show that it does not violate any fundamental limits on the spatial degrees of freedom.

Asymptotic throughput for large-scale wireless networks with general node density

We study the asymptotic throughput for a large-scale wireless ad hoc network consisting of n nodes under the generalized physical model. We directly compute the throughput of multicast sessions to unify the unicast and broadcast throughputs. We design two multicast schemes based on the so-called ordinary arterial road system and parallel arterial road system, respectively. Correspondingly, we derive the achievable multicast throughput by taking account of all possible cases of n s = ?(1) and 1 ? n d ? n ? 1, rather than only the cases of $$n_s=\Uptheta(n)$$ as in most related works, where n s and n d denote the number of sessions and the number of destinations of each session, respectively. Furthermore, we consider the network with a general node density $$\lambda \in [1,n]$$ , while the models in most related works are either random dense network (RDN) or random extended network (REN) where the density is ? = n and ? = 1, respectively, which further enhances the generality of this work. Particularly, for the special case of our results by letting ? = 1 and $$n_s=\Uptheta(n)$$ , we show that for some regimes of n d , the multicast throughputs achieved by our schemes are better than those derived by the well-known percolation-based schemes.

Scaling Laws of Multicast Capacity for Power-Constrained Wireless Networks under Gaussian Channel Model

We study the asymptotic networking-theoretic multicast capacity bounds for random extended networks (REN) under Gaussian channel model, in which all wireless nodes are individually power-constrained. During the transmission, the power decays along path with attenuation exponent α >; 2. In REN, n nodes are randomly distributed in the square region of side length √n. There are ns randomly and independently chosen multicast sessions. Each multicast session has nd + 1 randomly chosen terminals, including one source and nd destinations. By effectively combining two types of routing and scheduling strategies, we analyze the asymptotic achievable throughput for all ns = ω(1) and nd. As a special case of our results, we show that for ns = Θ(n), the per-session multicast capacity for REN is of order Θ(1/√ndn) when nd = O(n/(log n)a+1) and is of order Θ(1/nd · (log n)-n/2) when nd = Ω(n/log n).

Green Wave Sleep Scheduling: Optimizing Latency and Throughput in Duty Cycling Wireless Networks

Duty cycling or periodic sleep scheduling of RF transceivers of nodes in a wireless ad hoc or sensor network can significantly reduce energy consumption. This paper sheds light on the fundamental limits of the end-to-end data delivery latency and the per-flow throughput in a wireless network with multiple interfering flows, in the presence of "coordinated" duty cycling. We propose green wave sleep scheduling (GWSS) - inspired by synchronized traffic lights - for scheduling sleep-wake slots and routing data in a duty cycling wireless network, whose performance can approach the aforementioned limits. Particularly, we derive a general latency lower bound and show that GWSS is latency optimal on various structured topologies, such as the line, grid and the tree, at low traffic load. For an arbitrary network, finding a solution to the delay-efficient sleep scheduling problem is NP-hard. But for the 2D grid topology, we show that a non-interfering construction of GWSS is optimal in the sense of scaling laws of latency and capacity. Finally, using results from percolation theory, we extend GWSS to random wireless networks, where nodes are placed in a square area according to the Poisson point process. Aided by strong numerical evidence for a new conjecture on percolation on a semi-directed lattice that we propose, we demonstrate the latency optimality of GWSS on a random extended network, i.e., for an area-n random network with unit-density-Poisson distributed nodes, and a node-active (duty-cycling) rate p, GWSS can achieve a per-flow throughput scaling of T(n, p) = Ω(p/√n) bits/sec and latency D(n, p) scaling of O(√n) + O(1/p) hops/packet/flow.

Improved asymptotic multicast throughput for random extended networks

We study the asymptotic throughput for random extended networks, where n ad hoc nodes are randomly deployed in a square region R ( n ) = 0 , n 2 . We directly consider the multicast throughput to unify the unicast and broadcast throughput, and design a new multicast scheme under the generalized physical model based on the so-called secondary highways system. Taking account of all possible cases of n s = ω(1) and 1 ⩽ n d ⩽ n − 1, we derive the achievable multicast throughput, where n s and n d denote the number of sessions and the number of destinations of each session. We prove that for some cases in terms of n s and n d , our scheme achieves better throughput than the existing schemes.

Asymptotic Bounds of Information Dissemination in Power-Constrained Wireless Networks

Dissemination of common information through broadcasting is an integral part of wireless network operations such as query of interested events, resource discovery and code update. In this paper, we characterize the behavior of information dissemination in power-constrained wireless networks by defining two quantities, i.e., broadcast capacity and information diffusion rate and derive fundamental limits in both random extended networks. We find that using multihop relay, the rate of broadcasting continuous stream is thetas((log n)-alpha/2) in extended networks. Regardless of the density, information can diffuse at constant speed, i.e., thetas (1). Furthermore, we prove that a unified routing structure and MAC schedule can be devised that achieves order-optimal broadcasting performance in both delay and throughput. The theoretical bounds obtained and proof techniques are instrumental to the modeling and design of efficient wireless network protocols.