Scheduling for next generation WLANs: filling the gap between offered and observed data rates

In wireless networks, opportunistic scheduling is used to increase system throughput by exploiting multi-user diversity. Although recent advances have increased physical layer data rates supported in wireless local area networks (WLANs), actual throughput realized are significantly lower due to overhead. Accordingly, the frame aggregation concept is used in next generation WLANs to improve efficiency. However, with frame aggregation, traditional opportunistic schemes are no longer optimal. In this paper, we propose schedulers that take queue and channel conditions into account jointly, to maximize throughput observed at the users for next generation WLANs. We also extend this work to design two schedulers that perform block scheduling for maximizing network throughput over multiple transmission sequences. For these schedulers, which make decisions over long time durations, we model the system using queueing theory and determine users' temporal access proportions according to this model. Through detailed simulations, we show that all our proposed algorithms offer significant throughput improvement, better fairness, and much lower delay compared with traditional opportunistic schedulers, facilitating the practical use of the evolving standard for next generation wireless networks

Proportional fairness in wireless powered CSMA/CA based IoT networks

This paper considers the deployment of a hybrid wireless data/power access point in an 802.11-based wireless powered IoT network. The proportionally fair allocation of throughputs across IoT nodes is considered under the constraints of energy neutrality and CPU capability for each device. The joint optimization of wireless powering and data communication resources takes the CSMA/CA random channel access features, e.g. the backoff procedure, collisions, protocol overhead into account. Numerical results show that the optimized solution can effectively balance individual throughput across nodes, and meanwhile proportionally maximize the overall sum throughput under energy constraints.Comment: Accepted by Globecom 201

Life-Add: Lifetime Adjustable Design for WiFi Networks with Heterogeneous Energy Supplies

WiFi usage significantly reduces the battery lifetime of handheld devices such as smartphones and tablets, due to its high energy consumption. In this paper, we propose "Life-Add": a Lifetime Adjustable design for WiFi networks, where the devices are powered by battery, electric power, and/or renewable energy. In Life-Add, a device turns off its radio to save energy when the channel is sensed to be busy, and sleeps for a random time period before sensing the channel again. Life-Add carefully controls the devices' average sleep periods to improve their throughput while satisfying their operation time requirement. It is proven that Life-Add achieves near-optimal proportional-fair utility performance for single access point (AP) scenarios. Moreover, Life-Add alleviates the near-far effect and hidden terminal problem in general multiple AP scenarios. Our ns-3 simulations show that Life-Add simultaneously improves the lifetime, throughput, and fairness performance of WiFi networks, and coexists harmoniously with IEEE 802.11.Comment: This is the technical report of our WiOpt paper. The paper received the best student paper award at IEEE WiOpt 2013. The first three authors are co-primary author

Controlled Matching Game for Resource Allocation and User Association in WLANs

In multi-rate IEEE 802.11 WLANs, the traditional user association based on the strongest received signal and the well known anomaly of the MAC protocol can lead to overloaded Access Points (APs), and poor or heterogeneous performance. Our goal is to propose an alternative game-theoretic approach for association. We model the joint resource allocation and user association as a matching game with complementarities and peer effects consisting of selfish players solely interested in their individual throughputs. Using recent game-theoretic results we first show that various resource sharing protocols actually fall in the scope of the set of stability-inducing resource allocation schemes. The game makes an extensive use of the Nash bargaining and some of its related properties that allow to control the incentives of the players. We show that the proposed mechanism can greatly improve the efficiency of 802.11 with heterogeneous nodes and reduce the negative impact of peer effects such as its MAC anomaly. The mechanism can be implemented as a virtual connectivity management layer to achieve efficient APs-user associations without modification of the MAC layer

AP-STA association control for throughput maximization in virtualized WiFi networks

To manage and enable service customization among multiple internet service providers (ISPs) sharing the common physical infrastructure and network capacity in virtualized Wi-Fi networks, this paper models and optimizes access point-station (STA) association via airtime usage control. More specifically, an optimization problem is formulated on the STAs’ transmission probabilities to maximize the overall network throughput, while providing airtime usage guarantees for the ISPs. As the proposed optimization problem is inherently non-convex, an algorithm to reach the optimal solution is developed by applying monomial approximation and geometric programming iteratively. Based on the proposed 3-D Markov-chain model of the enhanced distributed channel access protocol, the detailed implementation of the optimal transmission probability of each STA is also discussed by manipulating medium access control parameters. The performance of the developed association and airtime control scheme is evaluated through numerical results. For both homogeneous and non-homogeneous STA distributions, numerical results reveal performance gains of the proposed algorithm in improving the throughput and keeping airtime usage guarantees