RESOURCE ALLOCATION AND EFFICIENT ROUTING IN WIRELESS NETWORKS

In wireless networks, devices (nodes) are connected by wireless links. An important issue is to set up high quality (high bandwidth) and efficient routing paths when one node wants to send packets to other nodes. Resource allocation is the foundation to guarantee high quality connections. In addition, it is critical to handle void areas in order to set up detour-free paths. Moreover, fast message broadcasting is essential in mobile wireless networks. Thus, my research includes dynamic channel allocation in wireless mesh networks, geographic routing in Ad Hoc networks, and message broadcasting in vehicular networks. The quality of connections in a wireless mesh network can be improved by equip- ping mesh nodes with multi-radios capable of tuning to non-overlapping channels. The essential problem is how to allocate channels to these multi-radio nodes. We develop a new bipartite-graph based channel allocation algorithm, which can improve bandwidth utilization and lower the possibility of starvation. Geographic routing in Ad Hoc networks is scalable and normally loop-free. However, traditional routing protocols often result in long detour paths when holes exist. We propose a routing protocol-Intermediate Target based Geographic Routing (ITGR) to solve this problem. The novelty is that a single forwarding path can be used to reduce the lengths of many future routing paths. We also develop a protocol called Hole Detection and Adaptive Geographic Routing, which identifies the holes efficiently by comparing the length of a routing path with the Euclidean distance between a pair of nodes. We then set up the shortest path based on it. Vehicles play an important role in our daily life. During inter-vehicle communication, it is essential that emergency information can be broadcast to surrounding vehicles quickly. We devise an approach that can find the best re-broadcasting node and propagate the message as fast as possible

Optimality of Treating Interference as Noise: A Combinatorial Perspective

For single-antenna Gaussian interference channels, we re-formulate the problem of determining the Generalized Degrees of Freedom (GDoF) region achievable by treating interference as Gaussian noise (TIN) derived in [3] from a combinatorial perspective. We show that the TIN power control problem can be cast into an assignment problem, such that the globally optimal power allocation variables can be obtained by well-known polynomial time algorithms. Furthermore, the expression of the TIN-Achievable GDoF region (TINA region) can be substantially simplified with the aid of maximum weighted matchings. We also provide conditions under which the TINA region is a convex polytope that relax those in [3]. For these new conditions, together with a channel connectivity (i.e., interference topology) condition, we show TIN optimality for a new class of interference networks that is not included, nor includes, the class found in [3]. Building on the above insights, we consider the problem of joint link scheduling and power control in wireless networks, which has been widely studied as a basic physical layer mechanism for device-to-device (D2D) communications. Inspired by the relaxed TIN channel strength condition as well as the assignment-based power allocation, we propose a low-complexity GDoF-based distributed link scheduling and power control mechanism (ITLinQ+) that improves upon the ITLinQ scheme proposed in [4] and further improves over the heuristic approach known as FlashLinQ. It is demonstrated by simulation that ITLinQ+ provides significant average network throughput gains over both ITLinQ and FlashLinQ, and yet still maintains the same level of implementation complexity. More notably, the energy efficiency of the newly proposed ITLinQ+ is substantially larger than that of ITLinQ and FlashLinQ, which is desirable for D2D networks formed by battery-powered devices.Comment: A short version has been presented at IEEE International Symposium on Information Theory (ISIT 2015), Hong Kon

On provision of resilient connectivity in cognitive unmanned aerial vehicles

Mobile ad-hoc network (MANET) can be established in the areas/scenarios where the infrastructure networks are either out of service or no more available. MANETs have a lot of applications in sensor networks. Generally, a MANET deploys mobile ground nodes to set up a network. However, there can be some severe scenarios such as flood, battlefield, rescue operations, etc. where these ground nodes cannot be deployed. In such cases, a network of unmanned aerial vehicles (UAVs) can be a more viable option. Normally, UAVs operates on IEEE L-Band, IEEE S-Band or ISM band. These bands are already overcrowded, therefore, UAVs will face the problem of the spectrum scarcity. To resolve this issue cognitive radio (CR) is a most promising technology. Hence, in this work, we focus on CR based UAVs. As CR is based on opportunistic spectrum access, therefore, it is quite possible that all UAVs do not have one single channel available to communicate with each other. They need to form clusters for their communication depending on the availability of the channel. However, channel availability is intermittent because of opportunistic spectrum access. This may result in reforming of the cluster again and again. To avoid this frequent re-clustering and to maintain connectivity among the UAVs, in this paper, we present a resilient clustering technique with a concept of introducing a backup channel for each cluster. Simulation results show the significance of the proposed technique

Reliable Broadcast over Cognitive Radio Networks: A Bipartite Graph-Based Algorithm

Cognitive radio (CR) is a promising technology that aims to enhance the spectrum utilisation by enabling unlicenced users to opportunistically use the vacant spectrum bands assigned to licenced users. Broadcasting is considered as a fundamental operation in wireless networks, as well as in cognitive radio networks (CRNs). The operation of most network protocols in the ad hoc network depends on broadcasting control information from neighbouring nodes. In traditional single-channel or multichannel ad hoc networks, due to uniform channel availability, broadcasting is easily implemented as nodes are tuned to a single common channel. On the contrary, broadcasting in CR ad hoc networks is both a challenging and complex task. The complexity emerges from the fact that different CR users might acquire different channels at different times. Consequently, this partitions the network into different clusters. In this chapter, the problem of broadcasting in ad hoc CR networks is presented, current solutions for the problem are discussed and an intelligent solution for broadcasting based on graph theory to connect different local topologies is developed

Intelligent spectrum management techniques for wireless cognitive radio networks

PhD ThesisThis thesis addresses many of the unique spectrum management chal- lenges in CR networks for the rst time. These challenges have a vital e ect on the network performance and are particularly di cult to solve due to the unique characteristics of CR networks. Speci cally, this thesis proposes and investigates three intelligent spectrum management tech- niques for CR networks. The issues investigated in this thesis have a fundamental impact on the establishment, functionality and security of CR networks. First, an intelligent primary receiver-aware message exchange protocol for CR ad hoc networks is proposed. It considers the problem of alleviat- ing the interference collision risk to primary user communication, explic- itly to protect primary receivers that are not detected during spectrum sensing. The proposed protocol achieves a higher measure of safeguard- ing. A practical scenario is considered where no global network topology is known and no common control channel is assumed to exist. Second, a novel CR broadcast protocol (CRBP) to reliably disseminate the broadcast messages to all or most of the possible CR nodes in the network is proposed. The CRBP formulates the broadcast problem as a bipartite-graph problem. Thus, CRBP achieves a signi cant successful delivery ratio by connecting di erent local topologies, which is a unique feature in CR ad hoc networks. Finally, a new defence strategy to defend against spectrum sensing data falsi cation attacks in CR networks is proposed. In order to identify malicious users, the proposed scheme performs multiple veri cations of sensory data with the assistance of trusted nodes.Higher Committee For Education Devel- opment in Iraq (HCED-Iraq

Combinatorial Network Optimization with Unknown Variables: Multi-Armed Bandits with Linear Rewards

In the classic multi-armed bandits problem, the goal is to have a policy for dynamically operating arms that each yield stochastic rewards with unknown means. The key metric of interest is regret, defined as the gap between the expected total reward accumulated by an omniscient player that knows the reward means for each arm, and the expected total reward accumulated by the given policy. The policies presented in prior work have storage, computation and regret all growing linearly with the number of arms, which is not scalable when the number of arms is large. We consider in this work a broad class of multi-armed bandits with dependent arms that yield rewards as a linear combination of a set of unknown parameters. For this general framework, we present efficient policies that are shown to achieve regret that grows logarithmically with time, and polynomially in the number of unknown parameters (even though the number of dependent arms may grow exponentially). Furthermore, these policies only require storage that grows linearly in the number of unknown parameters. We show that this generalization is broadly applicable and useful for many interesting tasks in networks that can be formulated as tractable combinatorial optimization problems with linear objective functions, such as maximum weight matching, shortest path, and minimum spanning tree computations