Resource management in QoS-aware wireless cellular networks

2011 Summer.Includes bibliographical references.Emerging broadband wireless networks that support high speed packet data with heterogeneous quality of service (QoS) requirements demand more flexible and efficient use of the scarce spectral resource. Opportunistic scheduling exploits the time-varying, location-dependent channel conditions to achieve multiuser diversity. In this work, we study two types of resource allocation problems in QoS-aware wireless cellular networks. First, we develop a rigorous framework to study opportunistic scheduling in multiuser OFDM systems. We derive optimal opportunistic scheduling policies under three common QoS/fairness constraints for multiuser OFDM systems--temporal fairness, utilitarian fairness, and minimum-performance guarantees. To implement these optimal policies efficiently, we provide a modified Hungarian algorithm and a simple suboptimal algorithm. We then propose a generalized opportunistic scheduling framework that incorporates multiple mixed QoS/fairness constraints, including providing both lower and upper bound constraints. Next, taking input queues and channel memory into consideration, we reformulate the transmission scheduling problem as a new class of Markov decision processes (MDPs) with fairness constraints. We investigate the throughput maximization and the delay minimization problems in this context. We study two categories of fairness constraints, namely temporal fairness and utilitarian fairness. We consider two criteria: infinite horizon expected total discounted reward and expected average reward. We derive and prove explicit dynamic programming equations for the above constrained MDPs, and characterize optimal scheduling policies based on those equations. An attractive feature of our proposed schemes is that they can easily be extended to fit different objective functions and other fairness measures. Although we only focus on uplink scheduling, the scheme is equally applicable to the downlink case. Furthermore, we develop an efficient approximation method--temporal fair rollout--to reduce the computational cost

Energy-efficient wireless communication

In this chapter we present an energy-efficient highly adaptive network interface architecture and a novel data link layer protocol for wireless networks that provides Quality of Service (QoS) support for diverse traffic types. Due to the dynamic nature of wireless networks, adaptations in bandwidth scheduling and error control are necessary to achieve energy efficiency and an acceptable quality of service. In our approach we apply adaptability through all layers of the protocol stack, and provide feedback to the applications. In this way the applications can adapt the data streams, and the network protocols can adapt the communication parameters

Centralized Rate Allocation and Control in 802.11-based Wireless Mesh Networks

Wireless Mesh Networks (WMNs) built with commodity 802.11 radios are a cost-effective means of providing last mile broadband Internet access. Their multihop architecture allows for rapid deployment and organic growth of these networks. 802.11 radios are an important building block in WMNs. These low cost radios are readily available, and can be used globally in license-exempt frequency bands. However, the 802.11 Distributed Coordination Function (DCF) medium access mechanism does not scale well in large multihop networks. This produces suboptimal behavior in many transport protocols, including TCP, the dominant transport protocol in the Internet. In particular, cross-layer interaction between DCF and TCP results in flow level unfairness, including starvation, with backlogged traffic sources. Solutions found in the literature propose distributed source rate control algorithms to alleviate this problem. However, this requires MAC-layer or transport-layer changes on all mesh routers. This is often infeasible in practical deployments. In wireline networks, router-assisted rate control techniques have been proposed for use alongside end-to-end mechanisms. We evaluate the feasibility of establishing similar centralized control via gateway mesh routers in WMNs. We find that commonly used router-assisted flow control schemes designed for wired networks fail in WMNs. This is because they assume that: (1) links can be scheduled independently, and (2) router queue buildups are sufficient for detecting congestion. These abstractions do not hold in a wireless network, rendering wired scheduling algorithms such as Fair Queueing (and its variants) and Active Queue Management (AQM) techniques ineffective as a gateway-enforceable solution in a WMN. We show that only non-work-conserving rate-based scheduling can effectively enforce rate allocation via a single centralized traffic-aggregation point. In this context we propose, design, and evaluate a framework of centralized, measurement-based, feedback-driven mechanisms that can enforce a rate allocation policy objective for adaptive traffic streams in a WMN. In this dissertation we focus on fair rate allocation requirements. Our approach does not require any changes to individual mesh routers. Further, it uses existing data traffic as capacity probes, thus incurring a zero control traffic overhead. We propose two mechanisms based on this approach: aggregate rate control (ARC) and per-flow rate control (PFRC). ARC limits the aggregate capacity of a network to the sum of fair rates for a given set of flows. We show that the resulting rate allocation achieved by DCF is approximately max-min fair. PFRC allows us to exercise finer-grained control over the rate allocation process. We show how it can be used to achieve weighted flow rate fairness. We evaluate the performance of these mechanisms using simulations as well as implementation on a multihop wireless testbed. Our comparative analysis show that our mechanisms improve fairness indices by a factor of 2 to 3 when compared with networks without any rate limiting, and are approximately equivalent to results achieved with distributed source rate limiting mechanisms that require software modifications on all mesh routers

Opportunistic transmission scheduling for next generation wireless communication systems with multimedia services

The explosive growth of the Internet and the continued dramatic increase for all wireless services are fueling the demand for increased capacity, data rates, and support of different quality of service (QoS) requirements for different classes of services. Since in the current and future wireless communication infrastructures, the performances of the various services are strongly correlated, as the resources are shared among them, dynamic resource allocation methods should be employed. With the demand for high data rate and support of multiple QoS, the transmission scheduling plays a key role in the efficient resource allocation process in wireless systems. The fundamental problem of scheduling the users\u27 transmissions and allocating the available resources in a realistic CDMA wireless system that supports multi-rate multimedia services, with efficiency and fairness, is investigated and analyzed in this dissertation. Our proposed approach adopts the use of dynamically assigned data rates that match the channel capacity in order to improve the system throughput and overcome the problems associated with the location-dependent and time-dependent errors and channel conditions, the variable system capacity and the transmission power limitation. We first introduce and describe two new scheduling algorithms, namely the Channel Adaptive Rate Scheduling (CARS) and Fair Channel Adaptive Rate Scheduling (FCARS). CARS exploits the channel variations to reach high throughput, by adjusting the transmission rates according to the varying channel conditions and by performing an iterative procedure to determine the power index that a user can accept by its current channel condition and transmission power. Based on the assignment of CARS and to overcome potential unfair service allocation, FCARS implements a compensation algorithm, in which the lagging users can receive compensation service when the corresponding channel conditions improve, in order to achieve asymptotic throughput fairness, while still maintaining all the constraints imposed by the system. Furthermore the problem of opportunistic fair scheduling in the uplink transmission of CDMA systems, with the objective of maximizing the uplink system throughput, while satisfying the users\u27 QoS requirements and maintaining the long-term fairness among the various users despite their different varying channel conditions, is rigorously formulated, and a throughput optimal fair scheduling policy is obtained. The corresponding problem is expressed as a weighted throughput maximization problem, under certain power and QoS constraints, where the weights are the control parameters that reflect the fairness constraints. With the introduction of the power index capacity it is shown that this optimization problem can be converted into a binary knapsack problem, where all the corresponding constraints are replaced by the users\u27 power index capacities at some certain system power index. It is then argued that the optimal solution can be obtained as a global search within a certain range, while a stochastic approximation method is presented in order to effectively identify the required control parameters. Finally, since some real-time services may demand certain amount of service within specific short span of time in order to avoid service delays, the problem of designing policies that can achieve high throughput while at the same time maintain short term fairness, is also considered and investigated. To this end a new Credit-based Short-term Fairness Scheduling (CSFS) algorithm, which achieves to provide short-term fairness to the delay-sensitive users while still schedules opportunistically the non-delay-sensitive users to obtain high system throughput, is proposed and evaluated

Resource Allocation in Relay-based Satellite and Wireless Communication Networks

A two-level bandwidth allocation scheme is proposed for a slotted Time-Division Multiple Access high data rate relay satellite communication link to provide efficient and fair channel utilization. The long-term allocation is implemented to provide per-flow/per-user Quality-of-Service guarantees and shape the average behavior. The time-varying short-term allocation is determined by solving an optimal timeslot scheduling problem based on the requests and other parameters. Through extensive simulations, the performance of a suitable MAC protocol with two-level bandwidth allocation is analyzed and compared with that of the existing static fixed-assignment scheme in terms of end-to-end delay and successful throughput. It is also shown that pseudo-proportional fairness is achieved for our hybrid protocol. We study rate control systems with heterogeneous time-varying propagation delays, based on analytic fluid flow models composed of first-order delay-differential equations. Both single-flow and multi-flow system models are analyzed, with special attention paid to the Mitra-Seery algorithm. The stationary solutions are investigated. For the fluctuating solutions, their dynamic behavior is analyzed in detail, analytically and numerically, in terms of amplitude, transient behavior, fairness and adaptability, etc.. Especially the effects of heterogeneous time-varying delays are investigated. It is shown that with proper parameter design the system can achieve stable behavior with close to pointwise proportional fairness among flows. Finally we investigate the resource allocation in 802.16j multi-hop relay systems with rate fairness constraints for two mutually exclusive options: transparent and non-transparent relay systems (T-RS and NT-RS). Single-Input Single-Output and Multi-Input Multi-Output antenna systems are considered in the links between the Base Station (BS) and Relay Stations (RS). 1 and 3 RSs per sector are considered. The Mobile Station (MS) association rule, which determines the access station (BS or RS) for each MS, is also studied. Two rules: Highest MCS scheme with the highest modulation and coding rate, and Highest (Mod) ESE scheme with the highest (modified) effective spectrum efficiency, are studied along with the optimal rule that maximizes system capacity with rate fairness constraints. Our simulation results show that the highest capacity is always achieved by NT-RS with 3 RSs per sector in distributed scheduling mode, and that the Highest (Mod) ESE scheme performs closely to the optimal rule in terms of system capacity

Cross-layer design for network performance optimization in wireless networks

In this dissertation, I use mathematical optimization approach to solve the complex network problems. Paper l and paper 2 first show that ignoring the bandwidth constraint can lead to infeasible routing solutions. A sufficient condition on link bandwidth is proposed that makes a routing solution feasible, and then a mathematical optimization model based on this sufficient condition is provided. Simulation results show that joint optimization models can provide more feasible routing solutions and provide significant improvement on throughput and lifetime. In paper 3 and paper 4, an interference model is proposed and a transmission scheduling scheme is presented to minimize the end-to-end delay. This scheduling scheme is designed based on integer linear programming and involves interference modeling. Using this schedule, there are no conflicting transmissions at any time. Through simulation, it shows that the proposed link scheduling scheme can significantly reduce end-to-end latency. Since to compute the maximum throughput is an NP-hard problem, efficient heuristics are presented in Paper 5 that use sufficient conditions instead of the computationally-expensive-to-get optimal condition to capture the mutual conflict relation in a collision domain. Both one-way transmission and two-way transmission are considered. Simulation results show that the proposed algorithms improve network throughput and reduce energy consumption, with significant improvement over previous work on both aspects. Paper 6 studies the complicated tradeoff relation among multiple factors that affect the sensor network lifetime and proposes an adaptive multi-hop clustering algorithm. It realizes the best tradeoff among multiple factors and outperforms others that do not. It is adaptive in the sense the clustering topology changes over time in order to have the maximum lifetime --Abstract, page iv