Wenxuan Guo

Maximizing throughput for overlaid cognitive radio networks

We consider a cognitive radio network in which a set of base stations make opportunistic spectrum access to support wireless subscribers within their covering cells. The spectrum of interest is divided into independent channels licensed to the primary users. Channel assignment and power control must be carried out in the cognitive network so that no excessive interference is caused to the primary users in the overlaid network. We are interested in the downlink channel assignment and power control problem for a cognitive radio network, with the objective of maximizing the total throughput of all secondary users. We first develop a mathematical model and present a Mixed Integer Linear Programming formulation, which is generally NP-hard. Subsequently, to obtain a suboptimal control scheme with lower complexity, we develop a distributed optimization algorithm that iteratively increases the overall cognitive radio network throughput. Through simulation results, we compare the performance of the distributed optimization algorithm with the optimal and validate its efficacy.

On relay node placement and assignment for two-tiered wireless networks

Wireless networks that operate on batteries are imposed with energy constraints and long distance communications between nodes are not desirable. Implementing Relay Nodes (RNs) can improve network capacity and save communication energy. A two-hop relay routing scheme is considered, in which the RNs are temporarily placed and have energy constraints. This paper investigates a joint optimization problem on Relay Node Placement (RNP) and route assignment for two-tiered wireless networks. A recursive Weighted Clustering Binary Integer Programming (WCBIP) algorithm is proposed to maximize the total number of information packets received at the Base Station (BS) during the network lifetime. We first present an optimization algorithm based on Binary Integer Programming (BIP) for Relay Node Assignment (RNA) with the current node locations. Subsequently, a weighted clustering algorithm is applied to move the RNs to the best locations to best serve their respectively associated Edge Nodes (ENs). The algorithm has the complexity of O(2n). The simulation results show that the proposed algorithm has significantly better performance than the other two relay placement schemes. Both theoretical analysis and practical design procedures are also presented with details.

On coverage and capacity for disaster area wireless networks using mobile relays

Public safety organizations increasingly rely on wireless technology to provide effective communications during emergency and disaster response operations. This paper presents a comprehensive study on dynamic placement of relay nodes (RNs) in a disaster area wireless network. It is based on our prior work of mobility model that characterizes the spatial movement of the first responders as mobile nodes (MNs) during their operations. We first investigate the COverage-oriented Relay Placement (CORP) problem that is to maximize the total number of MNs connected with the relays. Considering the network throughput, we then study the CApacity-oriented Relay Placement (CARP) problem that is to maximize the aggregated data rate of all MNs. For both coverage and capacity studies, we provide each the optimal and the greedy algorithms with computational complexity analysis. Furthermore, simulation results are presented to compare the performance between the greedy and the optimal solutions for the CORP and CARP problems, respectively. It is shown that the greedy algorithms can achieve near optimal performance but at significantly lower computational complexity.

Multicast communications in cognitive radio networks using directional antennas

This paper presents a study on multicast communications in cognitive radio networks CRNsusing directional antennas. The objective is to maximize the throughput of the CRN. The spectrum is divided into multiple channels and licensed to the primary network. While the CRN is accessing the spectrum, the interference power is carefully controlled to avoid impacting the operation of the primary network. The mathematical model is presented and subsequently formulated as a mixed integer non-linear programming MINLP problem, which is non-deterministic polynomial-time hard. Therefore, a greedy algorithm is designed to approximate the optimal performance. The MINLP problem is then relaxed and an upper bound is developed. Simulation results are presented to compare the performance of the greedy algorithm and the upper bound, which demonstrates the efficacy of the greedy algorithm as well as the tightness of the upper bound. Copyright

On throughput enhancement of multi-hop wireless networks using interference alignment

Interference alignment is a new technique recently proposed in physical layer wireless communications research, which purposely align the interference among multiple users thus increase the efficiency of channel use. This paper proposes a new method to enhance throughput of multi-hop wireless networks by utilizing interference alignment at physical layer. At first, it takes a simple network with only 6 nodes to demonstrate that interference alignment can achieve higher throughput. Subsequently, an optimization problem is formulated to maximize multi-hop wireless network throughput, which is a nonlinear programming (NLP) problem. Among that, finding the current transmission links can be transformed into maximal cliques of a graph. Furthermore, a branch-and-bound framework is provided to obtain the achievable bound of the NLP problem. Numerical results are presented to validate the algorithm and offer insights on the throughput enhancement brought by the interference alignment technique.

Relaying Packets in a Two-tiered Wireless Network Using Binary Integer Programming

Relay transmissions improve performance and save communication energy in wireless network. We present an optimal relay nodes assignment algorithm to maximize the number of information packets received at the sink for a two-tiered wireless network, in which the relay nodes are temporarily placed and have energy constraint. We first derive the optimal transmit power theory from relay node to sink node. Provided the limited energy at the relay nodes, we prove that the total transmission periods or the relay network lifetime is fixed. Subsequently, we determine the optimal dynamic association between edge nodes and relay nodes (multiple-to-one mapping) using binary integer programming (BIP). Experimental results show that the proposed method has significantly better performance than two other schemes in terms of the total number of information packets received at the sink. Combined with the optimal relay transmit power technique, the two-tiered wireless network can achieve the highest capacity considering the energy constraint of relay nodes.

Achieving capacity fairness for wireless mesh networks

This paper addresses a joint problem of power control and channel assignment within a wireless mesh network. A wireless mesh network is made up of two kinds of nodes: mesh routers (MRs) and user nodes (UNs). The MRs form a backbone network, while UNs receive data from the backbone network by connecting to the MRs via one hop. This paper aims to find the optimal joint solution of power control and channel assignment of the wireless mesh networks such that the minimum capacity of all links is maximized. We develop an upper bound for the objective by relaxing the integer variables and linearization. Subsequently, we put forward a heuristic approach to approximate the optimal solution, which tries to increase the minimal capacity of all links via setting tighter constraint and solving a binary integer programming problem. Simulation results show that solutions obtained by this algorithm are very close to the upper bounds obtained via relaxation, thus suggesting that the solution produced by the algorithm is near-optimal. Copyright

Distributed cross‐layer optimization for wireless regional area network‐based cognitive radio networks

This paper presents a study of a cross-layer design through joint optimization of spectrum allocation and power control for cognitive radio networks (CRNs). The spectrum of interest is divided into independent channels licensed to a set of primary users (PUs). The secondary users are activated only if the transmissions do not cause excessive interference to PUs. In particular, this paper studies the downlink channel assignment and power control in a CRN with the coexistence of PUs and secondary users. The objective was to maximize the total throughput of a CRN. A mathematical model is presented and subsequently formulated as a binary integer programming problem, which belongs to the class of non-deterministic polynomial-time hard problems. Subsequently, we develop a distributed algorithm to obtain sub-optimal results with lower computational complexity. The distributed algorithm iteratively improves the network throughput, which consists of several modules including maximum power calculation, excluded channel sets recording, base station throughput estimation, base station sorting, and channel usage implementation. Through investigating the impacts of the different parameters, simulation results demonstrates that the distributed algorithm can achieve a better performance than two other schemes. Copyright

Joint optimization of antenna orientation and spectrum allocation for cognitive radio networks

This paper presents a study on joint optimization of antenna orientation and spectrum allocation, with the objective of maximizing the total throughput of a cognitive radio network. The mathematical model is presented and subsequently formulated as a Mixed Integer Linear Programming problem. We obtain the optimal solution by adopting the branch and bound algorithm. Through simulation results, we investigate the impact of different parameters on the capacity performance of the cognitive radio network, including the transmit power and antenna directionality.

Optimal Relay Node Association for Two-Tiered Wireless Networks

Wireless networks that operate on batteries are imposed with energy constraints and long distance communications between nodes are not desirable. Implementing relay nodes can improve network capacity and save communication energy. A two-hop relay routing scheme is considered, in which the relay nodes are temporarily placed and have energy constraints. This paper investigates a joint optimization problem on relay node placement and route assignment for two-tiered wireless networks. A recursive weighted clustering binary integer programming (WCBIP) algorithm is proposed to maximize the total number of information packets received at the BS during the network lifetime. We first present an optimization algorithm based on binary integer programming (BIP) for relay node assignment with the current node locations. Subsequently, a weighted clustering algorithm is applied to move the relay nodes to the best locations to best serve their respectively associated edge nodes. The algorithm has the complexity of O(2n). The simulation results show that the proposed algorithm has significantly better performance than the other two relay placement schemes. Both theoretical analysis and practical design procedures are also presented with details.