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

Leveraging Physical Layer Capabilites: Distributed Scheduling in Interference Networks with Local Views

In most wireless networks, nodes have only limited local information about the state of the network, which includes connectivity and channel state information. With limited local information about the network, each node's knowledge is mismatched; therefore, they must make distributed decisions. In this paper, we pose the following question - if every node has network state information only about a small neighborhood, how and when should nodes choose to transmit? While link scheduling answers the above question for point-to-point physical layers which are designed for an interference-avoidance paradigm, we look for answers in cases when interference can be embraced by advanced PHY layer design, as suggested by results in network information theory. To make progress on this challenging problem, we propose a constructive distributed algorithm that achieves rates higher than link scheduling based on interference avoidance, especially if each node knows more than one hop of network state information. We compare our new aggressive algorithm to a conservative algorithm we have presented in [1]. Both algorithms schedule sub-networks such that each sub-network can employ advanced interference-embracing coding schemes to achieve higher rates. Our innovation is in the identification, selection and scheduling of sub-networks, especially when sub-networks are larger than a single link.Comment: 14 pages, Submitted to IEEE/ACM Transactions on Networking, October 201

On distributed scheduling for wireless networks with time-varying channels

textWireless scheduling is a fundamental problem in wireless networks that involves scheduling transmissions of multiple users in order to support data flows with as high rates as possible. This problem was first addressed by Tassuilas and Ephremides, resulting in the celebrated Back-Pressure network scheduling algorithm. This algorithm schedules network links to maximize throughput in an opportunistic fashion using instantaneous network state information (NSI), i.e., queue and channel state knowledge across the entire network. However, the Back-Pressure (BP) algorithm suffers from various drawbacks - (a) it requires knowledge of instantaneous NSI from the whole network, i.e. feedback about time-varying channel and queue states from all links of the network, (b) the algorithm requires solving a global optimization problem at each time to determine the schedule, making it highly centralized. Further, Back-pressure algorithm was originally designed for wireless networks where interference is modeled using protocol interference model. As recent break-throughs in full-duplex communications and interference cancelation techniques provide greatly increased capacity and scheduling flexibility, it is not clear how BP algorithm can be modified to improve the data rates and reduce the delay. In this thesis, we address the drawbacks of Back-Pressure algorithm to some extent. In particular, our first work provides a new scheduling algorithm (similar to BP) that allows users to make individual decisions (distributed) based on heterogeneously delayed network state information (NSI). Regarding the complexity issue, in our second work, we analyze the performance of the greedy version of BP algorithm, known as Greedy Maximal Scheduling (GMS) and understand the effect of channel variations on the performance of GMS. In particular, we characterize the efficiency ratio of GMS in wireless networks with fading. In our third and fourth work, we propose and analyze new scheduling algorithms that can benefit from new advancements in interference cancelation techniques.Electrical and Computer Engineerin

Local Greedy Approximation for Scheduling in Multi-hop Wireless Networks

In recent years, there has been a significant amount of work done in developing low-complexity scheduling schemes to achieve high performance in multi-hop wireless networks. A centralized sub-optimal scheduling policy, called Greedy Maximal Scheduling (GMS) is a good candidate because its empirically observed performance is close to optimal in a variety of network settings. However, its distributed realization requires high complexity, which becomes a major obstacle for practical implementation. In this paper, we develop simple distributed greedy algorithms for scheduling in multi-hop wireless networks. We reduce the complexity by relaxing the global ordering requirement of GMS, up to near-zero. Simulation results show that the new algorithms approximate the performance of GMS, and outperform the state-of-the-art distributed scheduling policies