Cross-Layer Capacity Estimation and Throughput Maximization in Wireless Networks

We study the problem of throughput maximization in multi-hop wireless networks with end-to-end delay constraints for each session. This problem has received much attention starting with the work of Grossglauser and Tse (2002), and it has been shown that there is a significant tradeoff between the end-to-end delays and the total achievable rate. We develop algorithms to compute such tradeoffs with provable performance guarantees for arbitrary instances, with general interference models. Given a target delay-bound Δ(c) for each session c, our algorithm gives a stable flow vector with a total throughput within a factor of O (equation) of the maximum, so that the per-session (end-to-end) delay is O (equation), where Δ <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">m</inf> = max <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">c</inf> {Δ(c)}; note that these bounds depend only on the delays, and not on the network size, and this is the first such result, to our knowledge.

Efficient operation of wireless networks requires distributed routing and scheduling algorithms that take into account interference constraints. Recently, a few algorithms for networks with primary- or secondary-interference constraints have been developed. Due to their distributed operation, these algorithms can achieve only a guaranteed fraction of the maximum possible throughput. It was also recently shown that if a set of conditions (known as Local Pooling) is satisfied, simple distributed scheduling algorithms achieve 100% throughput. However, previous work regarding Local Pooling focused mostly on obtaining abstract conditions and on networks with single-hop interference or single-hop traffic. In this paper, we identify several graph classes that satisfy the Local Pooling conditions, thereby enabling the use of such graphs in network design algorithms. Then, we study the multihop implications of Local Pooling. We show that in many cases, as the interference degree increases, the Local Pooling conditions are more likely to hold. Consequently, although increased interference reduces the maximum achievable throughput of the network, it tends to enable distributed algorithms to achieve 100% of this throughput. Regarding multihop traffic, we show that if the network satisfies only the single-hop Local Pooling conditions, distributed joint routing and scheduling algorithms are not guaranteed to achieve maximum throughput. Therefore, we present new conditions for Multihop Local Pooling, under which distributed algorithms achieve 100% throughout. Finally, we identify network topologies in which the conditions hold and discuss the algorithmic implications of the results.

We develop a distributed throughput-optimal power allocation algorithm in wireless networks. The study of this problem has been limited due to the nonconvexity of the underlying optimization problems that prohibits an efficient solution even in a centralized setting. By generalizing the randomization framework originally proposed for input queued switches to SINR rate-based interference model, we characterize the throughput-optimality conditions that enable efficient and distributed implementation. Using gossiping algorithm, we develop a distributed power allocation algorithm that satisfies the optimality conditions, thereby achieving (nearly) 100 percent throughput. We illustrate the performance of our power allocation solution through numerical simulation.

In this paper, we study node connectivity in multi-hop wireless networks. Nodal degree of connectivity as one of the fundamental graph properties is the basis for the study of network connectivity and has been a major research issue in multi-hop wireless networks. We use Random Geometric Graphs (RGG) to model multi-hop wireless networks and present a non-asymptotic analysis assuming bounded area and finite number of nodes. We assume random uniformly scattered nodes in a square-shaped bounded area. We derive a closed-form formula for the expected value of node degree of connectivity and propose an approximation algorithm for degree distribution in multi-hop wireless networks. Our extensive simulation results confirm that the proposed non-asymptotic analyses are quite accurate.

Wireless multi-hop local area networks use in general scheduling schemes that assume the network capacity to be known. Indeed in most of the throughput-optimal algorithms the sources are assumed to send at a rate within the capacity region. However, measurements made on real deployments show that the network capacity is usually difficult to characterize and also time-varying. It is therefore important to understand how the network behaves when the sources attempt to transmit at a rate above capacity. Toward this goal, we show 3-phase regime in the effect of the input rate λ on the end-to-end throughput μ of a multi-hop network. First, when λ is smaller than a threshold λ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> , μ is an increasing function of λ. Second, when λ is larger than another threshold λ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> > λ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> , μ is independent of λ. Third, when λ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> <; λ <; λ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> , μ decreases with λ. To understand this phenomenon, we capture the relation between the end-to-end throughput and the queue stability with a mathematical model that allows us to explain and derive the exact values of the transition points λi. We then validate experimentally our simulation results with measurements on a testbed composed of five wireless routers.

The increasing use of multi-hop wireless networks and the growing demand of bandwidth-intensive multimedia applications are the driving force to explore innovative techniques that can enhance the capacity of multi-hop wireless networks. The commonly used omni-directional antennas limit the spatial reusability of the wireless channel and hence reduce the available capacity of wireless networks. On the contrary, bandforming antennas, that enable directional transmissions and receptions, can overcome the aforementioned limitation. With the recent advances in signed processing and antenna technologies, smart beamforming antennas have become feasible in compact sizes and suitable prices and hence pertinent to multi-hop wireless networks. However, lack of appropriate control over the antenna beamforming may deteriorate the overall performance even below the level achieved by omni-directional antennas. Moreover, beamforming antennas introduce unprecedented challenges including deafness and directional hidden terminal problems. Hence, it is important to design efficient mechanisms for both Medium Access Control (MAC) and routing to deal with these challenges that hinder the full exploitation of spatial reusability offered by smart beamforming antennas. In this dissertation, we develop an analytical framework for modeling directional contention-based MAC protocols, which is, up to our knowledge, the first model to include deafness in the analysis. We show that deafness can severely limit the network capacity. Based on the insights gained from our analysis of the limitations of the existing solutions, we propose a novel opportunistic directional MAC protocol for multi-hop wireless networks with beamforming antennas. The proposed MAC protocol employs a new backoff mechanism that aims at minimizing the unnecessary idle waiting time, which is a key factor in leveraging the spatial reuse. Through extensive simulations, we demonstrate that the proposed MAC protocol enhances the performance in terms of throughput, delay, packet delivery ratio and fairness. We have also addressed the question about the theoretical capacity gain achieved by beamforming antennas. We derive a generic interference model that can accommodate any antenna radiation pattern and show that the capacity gain is significant even when realistic antenna radiation patterns are used. Since smart beamforming antennas can significantly spare the network resources, they can be utilized to provide Quality of Service (QoS) guarantees. We study the bandwidth-guaranteed routing problem in contention-based multi-hop wireless networks with beamforming antennas. We first present an analysis for the wireless links interdependencies in a contention-based environment in the presence of beamforming, which helps in our formulation of the QoS routing problem as a mixed-integer non-linear optimization problem. We then propose a routing and admission control algorithm for its solution. Our simulation results demonstrate the accuracy of our analysis and the ability of our proposed algorithm to find bandwidth-guaranteed routes. In summary, the analysis and design approaches, adopted in this dissertation, enhance the throughput of multi-hop wireless networks by grasping the transmission opportunities offered by smart beamforming antennas while dealing with the beamforming-related challenges at the MAC and network layers, which otherwise limit the spatial reusability of the wireless channel.

The key factor of influencing the network capacity performance is the effect of interference power of receiving nodes, which is obtained from the other transmitting nodes in multihop wireless networks (MWNs) that are simultaneously using the same channel. Minimizing total interference power can improve overall network capacity and reduce total energy consumption. In this paper, we propose a consensus transmit power control (CTPC) algorithm to maximize end-to-end throughput in MWNs. The CTPC algorithm tunes the nodes' transmit powers to maximize the average end-to-end throughput with a consensus coefficient. Simulation results reveal that the CTPC algorithm enables all the traffic flows to accomplish the maximum average end-to-end throughput. At the same time, the total interference power and the total power consumption are decreasing. Only in the dense MWNs, under usual threshold of received signal strength indicator (RSSI) setting, the CTPC algorithm cannot achieve good performance. In addition, an advanced wmediumd emulator over the StarBED testbed is used to further verify the performance evaluation of CTPC algorithm.

This paper addresses the Quality of Service (QoS) degradation problem of wireless relay node failures in multihop Worldwide interoperable Microwave Access (WiMAX) and Long Term Evolution (LTE) networks. In general, node protection in a communication network increases the reliability of the traffic flow from source to destination. For wireless networks, implementing the traditional 1+1 protection scheme increases the capital cost, as resources cannot be fully utilized. On the other hand, the design and implementation of the 1:N protection scheme in wireless networks for greater value of N (> 2) is very difficult, due to wireless network coverage and the physical layer design. To overcome the above drawbacks, a technique based on network coding is proposed for node protection in multihop wireless networks. In multihop wireless networks, few research efforts are concentrated on node protection schemes using network coding. Moreover, to best of our knowledge, no reports have been published on measuring the QoS performance for node protection in 4G wireless networks using network coding. In this paper, we first describe the node protection scheme using XOR network coding for multihop 4G wireless networks. Then, we measure the QoS performance, such as packet delivery ratio (PDR), latency and jitter, for different scenarios. The scenarios include a failure of a single relay node and failures of two relay nodes with and without our protection scheme and user's mobility. The simulation results show that the QoS performance with protection against a single relay node failure and failures of two relay nodes are very close to that of no failure scenario, while the network reliability increases due to the protection mechanism. Also, we report a decoding problem in multihop wireless networks using XOR network coding.

The backpressure scheduling algorithm for multihop wireless networks is known to be throughput optimal, but it requires each node to maintain per-destination queues. Recently, a clever generalization of processor sharing has been proposed which is also throughput optimal, but which only uses per-link queues. Here we propose another algorithm called Queue Proportional Rate Allocation (QPRA) which also only uses per-link queues, and allocates service rates to links in proportion to their queue-lengths and employs the Serve-In-Random-Order (SIRO) discipline within each link. Through fluid limit techniques and using a novel Lyapunov function, we show that the QPRA achieves the maximum throughput. We demonstrate an advantage of QPRA by showing that, for the so-called primary interference model, it is able to develop a low-complexity scheduling scheme which approximates QPRA and achieves a constant fraction of the maximum throughput region, independent of network size.

The performance of a multihop wireless network is typically affected by the interference caused by transmissions in the same network. In a statistical fading environment, the interference effects become harder to predict. Information sources in a multihop wireless network can improve throughput and delay performance of data streams by implementing interference-aware packet injection mechanisms. Forcing packets to wait at the head of queues and coordinating packet injections among different sources enable effective control of copacket interference. In this paper, throughput and delay performance in interference-limited multihop networks is analyzed. Using nonlinear probabilistic hopping models, waiting times which jointly optimize throughput and delay performances are derived. Optimal coordinated injection strategies are also investigated as functions of the number of information sources and their separations. The resulting analysis demonstrates the interaction of performance constraints and achievable capacity in a wireless multihop network.

Interference neutralization (IN) is an interference management technique that allows simultaneous transmission of multiple links by nullifying their mutual interference in the air via cooperation among the transmitters. Although IN has been studied from information theoretic perspective, its potential for a general multi-hop wireless network has not been explored. The goal of this paper is to understand IN in a multi-hop wireless network from networking perspective. We first establish an IN reference model. Based on this reference model, we develop a set of feasibility constraints for a subset of links to be active simultaneously. By identifying each eligible neutralization node (called neut), we study IN in a general multi-hop network and develop a set of necessary constraints to characterize neut selection, IN, and scheduling. These constraints allow us to study the performance of multi-hop networks without the need of getting involved into onerous signal design issues at the physical layer. Finally, we apply our IN model and constraints to study a throughput maximization problem and show that the use of IN can generally increase network throughput. In particular, throughput gain is most significant when the node density increases.

In this paper, we address the rate control problem in a multihop random access wireless network, with the objective of achieving proportional fairness amongst the end-to-end sessions. The problem is considered in the framework of nonlinear optimization. Compared with its counterpart in a wired network where link capacities are fixed, rate control in a multihop random access network is much more complex and requires joint optimization at both the transport and link layers. This is due to the fact that the attainable throughput on each link in the network is "elastic" and is typically a nonconvex and nonseparable function of the transmission attempt rates. Two cross-layer algorithms, a dual-based algorithm and a penalty-based algorithm, are proposed in this paper to solve the rate control problem in a multihop random access network. Both algorithms can be implemented in a distributed manner, and work at the link layer to adjust link attempt probabilities and at the transport layer to adjust session rates. We prove rigorously that the two proposed algorithms converge to the globally optimal solutions. Simulation results are provided in support of our conclusions.

We propose and evaluate the performance of communication algorithms for the NP-hard transmission time minimisation problem on multihop wireless networks modelled by directed graphs with multiple channels. We derive a lower bound for the minimum transmission time so that our heuristic solutions can be compared with optimal schedules. We present one randomised routing algorithm and nine heuristic transmission scheduling algorithms and demonstrate by extensive simulations on random multihop wireless networks that all these transmission scheduling algorithms have average-case performance reasonably close to that of optimal schedules. Furthermore, we show that the performance of our algorithms for undirected networks is significantly better than the pipelined breadth-first search tree algorithm by exploiting more transmission concurrency. We indicate that our transmission scheduling algorithms can be easily adapted to solve the related NP-hard throughput maximisation problem and present and compare their average-case performance by extensive simulations on random multihop wireless networks. We also demonstrate simulation data on the impact of the transmission power on transmission schedule length.

Full-duplex (FD) wireless communication improves the attainable spectral efficiency of the wireless network with the simultaneous transmission and reception over the same frequency channel at a single timeslot. However, the effect of self-interference (SI) and inter-user interference (IUI) become crucial to take into consideration compared to the current half-duplex system. Many researches have been studied to suppress the SI and IUI, to design the medium access control (MAC) protocol, and to propose resource management techniques for realizing the FD system and truly achieving the double transmission capacity in the network. In this paper, we propose a novel FD MAC protocol with a mixture of concurrent and sequential transmission scheme, namely FD-MCST, for maximizing the transmission capacity in multihop wireless networks. Through FD-MCST, the transmitting node can cooperatively share the transmission capacity status for maximizing the network capacity. As a result, numerical simulations reveal that the proposed FD-MCST can accomplish a higher achievable network capacity of up to 1.7 times and nearly twice the achievable throughput with a reasonable amount of achievable transmission overhead about 7.7%, compared to the existing FD MAC protocols.

Information-theoretic broadcast channels (BCs) and multiple-access channels (MACs) enable a single node to transmit data simultaneously to multiple nodes, and multiple nodes to transmit data simultaneously to a single node, respectively. In this paper, we address the problem of link scheduling in multihop wireless networks containing nodes with BC and MAC capabilities. We first propose an interference model that extends protocol interference models, originally designed for point-to-point channels, to include the possibility of BCs and MACs. Due to the high complexity of optimal link schedulers, we introduce the Multiuser Greedy Maximum Weight algorithm for link scheduling in multihop wireless networks containing BCs and MACs. Given a network graph, we develop new local pooling conditions and show that the performance of our algorithm can be fully characterized using the associated parameter, the multiuser local pooling factor. We provide examples of some network graphs, on which we apply local pooling conditions and derive the multiuser local pooling factor. We prove optimality of our algorithm in tree networks and show that the exploitation of BCs and MACs improve the throughput performance considerably in multihop wireless networks.