Algorithmic Aspects of Communications in Multihop Wireless Networks with MIMO Links

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.

In this paper, we study cross-layer design for rate control in multihop wireless networks. In our previous work, we have developed an optimal cross-layered rate control scheme that jointly computes both the rate allocation and the stabilizing schedule that controls the resources at the underlying layers. However, the scheduling component in this optimal cross-layered rate control scheme has to solve a complex global optimization problem at each time, and hence is too computationally expensive for online implementation. In this paper, we study how the performance of cross-layer rate control can be impacted if the network can only use an imperfect (and potentially distributed) scheduling component that is easier to implement. We study both the case when the number of users in the system is fixed and the case with dynamic arrivals and departures of the users, and we establish desirable results on the performance bounds of cross-layered rate control with imperfect scheduling. Compared with a layered approach that does not design rate control and scheduling together, our cross-layered approach has provably better performance bounds, and substantially outperforms the layered approach. The insights drawn from our analyses also enable us to design a fully distributed cross-layered rate control and scheduling algorithm for a restrictive interference model.

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.

Topology control in multi-hop wireless networks is a technique used to control nodes' activities to construct a topology with an acceptable level of network connectivity while minimizing energy consumption. It can be broadly classified into two main paradigms which are State Scheduling and Transmission Power Control. Both of them have received lots of attention from many researchers for decades. According to Transmission Power Control technique, most of them take into account only one-hop neighbor information to optimize transmission power and control topology in multi-hop wireless networks. In this paper, an energy efficient topology control based on both one-hop and two-hop neighbor information is proposed to reduce energy consumption without degrading network performances. A number of simulation scenarios are constructed in this work to study energy consumption as well as other network performances that are end-to-end delay, throughput, and packet delivery ratio of the proposed algorithm.

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.

Link quality measurement (LQM), i.e. packet reception ratio (PRR) measurement, is becoming an indispensable component in multihop wireless networks. However, in all the existing LQM mechanisms, a common fact is that a node's knowledge about the forward PRR from itself to its neighbor is informed by the neighbor. On the one hand, this receiver- dependent measurement provides accurate and timely updates on the link quality. On the other hand, it opens up a door for a malicious node to easily report a false measurement result to mislead the routing decision and degrade the system performance. In this paper, we analyze the security vulnerabilities in the existing LQM mechanisms and propose an efficient broadcast- based secure LQM (SLQM) mechanism, which prevents the malicious receiver from reporting a higher PRR than the actual one. We analyze the security strength and the cost of the proposed mechanism. Simulation results show that even when there are only 10% malicious nodes in the network, the average end-to-end throughput can be degraded by 50% compared with the normally operated network, which demonstrates the importance of employing SLQM mechanisms. To the best of our knowledge, this is the first work addressing the SLQM problem in multihop wireless networks.

We consider the problem of joint routing, scheduling and power control in multi-hop wireless networks. We use a linear relation between link capacity and signal to interference noise ratio in our formulation. In a previous work, using a duality approach, the optimal link scheduling and power control that minimizes the total average transmission power is found. We formulate this problem as a linear programming problem with exponential number of constraints. To cope with the exponential number of constraints, we propose an iterative algorithm based on the cutting plane method. The separation oracle for the cutting plane algorithm turns out to be an element-wise concave optimization problem that can be effectively solved using branch and bound algorithm. We extend the same method to find the optimal routing scheduling and power control. Simulation results show that this methodology is more efficient and scalable compare to the previously proposed algorithm.

The definition of new radio network topologies and deployment concepts capable of providing a ubiquitous radio coverage area for beyond 3G systems is one of the main objectives of the WINNER project [1]. Within this context, routing and forwarding algorithms for infrastructure-based multi-hop networks are investigated. We first present a new mathematical model of the routing problem in infrastructure-based multi-hop wireless networks that takes into account QoS requirements considering bandwidth constraints. Since the characteristics of such new networks allow to control the path selection of each flow, we then propose a new routing algorithm based on a heuristic. Finally, to show the performance of the proposed algorithm several simulation results are presented.

The authors address the problem of link activation or scheduling in multihop packet radio networks, a contention-free form of channel access that is appropriate for many military communication applications. This problem, in almost all of its forms, is a combinatorial-optimization problem of high complexity. They approach this problem by the use of a Hopfield neural network model in which the method of Lagrange multipliers is used to dynamically vary the values of the coefficients used in the connection weights. Extensive software simulation results demonstrate the effectiveness of this approach in producing schedules of optimal length. Issues associated with the extension of this approach to the joint routing/scheduling problem are discussed. >

Gossiping is to broadcast the message of every node to all the other nodes in multi-hop wireless networks (MWNs). This operation plays an important role and is widely used in MWNs. Interference-aware gossiping scheduling (IAGS) aims to provide an interference-free scheduling for gossiping with the minimum latency. Previous work on IAGS mostly assumes that nodes are always active, and thus is not suitable for duty-cycled scenarios. In this paper, we investigate the IAGS problem in uncoordinated duty-cycled multi-hop wireless networks (IAGS-UDC problem) under protocol interference model and unbounded-size message model. We prove that the IAGS-UDC problem is NP-hard. We propose a novel approximation algorithm called MILD for this problem. The MILD algorithm achieves an approximation ratio of 3β 2(Δ + 6)|T|, where β is \(\lceil \frac{2}{3}(\alpha+2)\rceil\), α denotes the ratio of the interference radius to the transmission radius, Δ denotes the maximum node degree of the network, and |T| denotes the number of time-slots in a scheduling period. Moreover, the number of transmissions scheduled by the MILD algorithm is at most 3 times as large as the minimum number of transmissions.KeywordsGossiping schedulinginterferenceduty cyclemulti-hop wireless networks

In multi-hop wireless networks, maximizing network utility by joint congestion control and scheduling has drawn much research interest, and significant progress has been made that has yielded much insight. However, in attempting to maximize network utilization, most scheduling mechanisms proposed in earlier works are too complicated to be implemented in wireless devices. One traditional approach to address complexity is to approximate the optimal but complex solution by a feasible solution that can provide a certain performance guarantee. In this paper, we suggest an alternative approach that simplifies the optimization problem itself in such a way that the solution of the new problem is guaranteed to be a fraction of the optimal solution of the original problem. The fraction depends on the “interference degree” of the network. Based on the simplified model, we propose a scheme which combines congestion control and random access MAC. We subsequently analyze its theoretical performance, and prove that the algorithm guarantees stability, and asymptotically converges to the near-optimal operational point. Future work is needed to investigate the mechanism by which such a scheme can be implemented.

This paper addresses the flow allocation problem in multi-hop wireless networks. We define and formulate a new interference model, referred to as the Node-based Interference Model, to better capture the behavior of medium access control protocols and the physical layer interference issues. Based on this model, we formulate the problem as a cross-layer network utility maximization problem that considers the coordination of the transport, MAC and physical layers, and avoid the maximum clique or independent set enumeration approach as adopted in most of the existing work. The objective of the problem is to maximize the aggregate network throughput while maintaining the fairness among flows. We then propose a gradient-based flow allocation algorithm by using the duality approach, and analyze the rate of convergence to the optimum for the proposed algorithm. The simulation results show that the proposed algorithm can rapidly converge to the optimum, and can also rapidly adapt to the changes in network topology and routing paths in different flow scenarios.

Fair resource allocation for end-to-end flows is an important yet challenging problem in multi-hop wireless networks. Recent research on fair resource allocation mainly focuses on two directions: 1) theoretical methods for joint optimization of scheduling and rate allocation, which are inherently hard to implement; 2) heuristic rate allocation solutions, which are practical for implementation, but simplify the scope of resource sharing regions using different neighborhood models. One key question that remains unanswered is how well these heuristic neighborhood-aware rate allocation solutions approximate the fair point defined in the theoretical optimal resource allocation framework. To evaluate the impact of different neighborhood models on end-to-end fairness, we first establish a baseline fairness model (i.e., proportional fairness) using the price-based resource allocation framework. In this framework, price represents the cost of the resource usage incurred by unit flow. The rate of a flow is directly linked to its price, which is the aggregated price of the links it traverses. The link price is the sum of the prices of all the resource sharing regions which it belongs to. Obviously, when the resource sharing regions are approximated by different neighborhood models in the heuristic solutions, link prices will manifest as different values. To quantify the deviations of these heuristic neighborhood-aware solutions from the baseline proportional fairness model, we introduce a normalized fairness index model. Six different neighborhood models are evaluated. Our study makes two significant observations: 1) symmetric knowledge on the construction of a neighborhood is important in achieving fairness. Such a knowledge has not been considered in any of the existing neighborhood-aware rate allocation algorithms; 2) while 1-hop neighborhood information brings noticeable gain in fairness, the knowledge of 2-hop neighborhood information does not necessarily bring additional benefit.

In this paper, we study the exposed terminal problem in multi-hop wireless networks with log-normal shadowing channels. Assuming that location information is known, we first calculate the success probability for the concurrent transmissions from exposed nodes. We then propose a new MAC protocol which schedules concurrent transmissions in the presence of log- normal shadowing, thus mitigating the exposed terminal problem and increasing network throughput. The performance of the proposed protocol is evaluated with ns-2 simulations, and it is shown to achieve considerable improvements in both end-to-end throughput and delay over the IEEE 802.11 MAC.

We address the multicast problem in a wireless multihop network in the presence of errors. Finding the multicast schedule that minimizes the expected number of transmissions, while accounting for both the wireless broadcast advantage (WBA) and the wireless unreliable transmission (WUT) characteristics, has not been solved optimally before. We formally define the problem and propose an initial algorithm of non-polynomial complexity to obtain the optimal solution. The algorithm starts by transforming the wireless network topology into an auxiliary expanded graph that captures the WBA property, and assigning appropriate weights to the links so as to capture the WUT property. The proposed transformation is interesting on its own merit, since it permits us to consider only point-to-point transmissions (as in wireline networks) in the expanded graph, instead of the point-to-multipoint transmissions present in the original wireless network, and can also be useful in other optimization problems some of which we briefly describe. By solving the minimum Steiner tree problem on the expanded graph we obtain the optimal multicast solution for the initial graph. Since the optimal algorithm is of non-polynomial complexity, we also propose a number of heuristic algorithms. In particular, we first present a truncated graph transformation and then describe two heuristic algorithms for obtaining the multicast schedule. Simulation results show that the proposed heuristics have performance close to that of the optimal algorithm, at least for the instances for which we were able to track optimal solutions, while outperforming other heuristic multicast algorithms.