Longest-queue-first scheduling under SINR interference model

We investigate the performance of longest-queue-first (LQF) scheduling (i.e., greedy maximal scheduling) for wireless networks under the SINR interference model. This interference model takes network geometry and the cumulative interference effect into account, which, therefore, capture the wireless interference more precisely than binary interference models. By employing the ρ-local pooling technique, we show that LQF scheduling achieves zero throughput in the worst case. We then propose a novel technique to localize interference which enables us to decentralize the LQF scheduling while preventing it from having vanishing throughput in all network topologies. We characterize the maximum throughput region under interference localization and present a distributed LQF scheduling algorithm. Finally, we present numerical results to illustrate the usefulness and to validate the theory developed in the paper.United States. Army Research Office. Multidisciplinary University Research Initiative (Grant W911NF-08-1-0238)National Science Foundation (U.S.) (Grant CNS-0915988)United States. Defense Threat Reduction Agency (Grant HDTRA1-07-1-0004

A Greedy Link Scheduler for Wireless Networks with Fading Channels

We consider the problem of link scheduling for wireless networks with fading channels, where the link rates are varying with time. Due to the high computational complexity of the throughput optimal scheduler, we provide a low complexity greedy link scheduler GFS, with provable performance guarantees. We show that the performance of our greedy scheduler can be analyzed using the Local Pooling Factor (LPF) of a network graph, which has been previously used to characterize the stability of the Greedy Maximal Scheduling (GMS) policy for networks with static channels. We conjecture that the performance of GFS is a lower bound on the performance of GMS for wireless networks with fading channel

Understanding Noise and Interference Regimes in 5G Millimeter-Wave Cellular Networks

With the severe spectrum shortage in conventional cellular bands, millimeter-wave (mmWave) frequencies have been attracting growing attention for next-generation micro- and picocellular wireless networks. A fundamental and open question is whether mmWave cellular networks are likely to be noise- or interference-limited. Identifying in which regime a network is operating is critical for the design of MAC and physical-layer procedures and to provide insights on how transmissions across cells should be coordinated to cope with interference. This work uses the latest measurement-based statistical channel models to accurately assess the Interference-to-Noise Ratio (INR) in a wide range of deployment scenarios. In addition to cell density, we also study antenna array size and antenna patterns, whose effects are critical in the mmWave regime. The channel models also account for blockage, line-of-sight and non-line-of-sight regimes as well as local scattering, that significantly affect the level of spatial isolation