You-En Lin

On Using Interference-Aware Spectrum Sensing for Dynamic Spectrum Access in Cognitive Radio Networks

Spectrum sensing is an important step toward enabling dynamic spectrum access in cognitive radio networks. To ensure that primary users are properly protected while maximizing the performance of secondary users, most related work considers the metrics of probabilities of missed detection and false alarm for determining optimal spectrum sensing parameters. In this paper, we argue that spectrum sensing based entirely on the two metrics is unable to maximize spectrum utilization for dynamic spectrum access. We show that, to meet the requirement of the probability of missed detection, conventional spectrum sensing techniques can unnecessarily increase the probability of false alarm in scenarios with good spectrum reuse opportunity, thus lowering the ability to leverage spectrum holes. To address this problem, we define the probability of interference and propose a new metric for spectrum sensing to consider both the probabilities of interference and missed detection. We first investigate the problem of optimal spectrum hole discovery for a single secondary user based on the proposed metric, and then extend to the problem of cooperative spectrum sensing among a group of secondary users. Compared against conventional sensing techniques presented in related work, we show through simulations that interference-aware spectrum sensing can potentially result in better utilization of the spectrum by allowing the secondary user to maximize its transmission opportunity without sacrificing the desired degree of protection for primary users.

Design of Power Control Protocols for Spectrum Sharing in Cognitive Radio Networks: A Game-Theoretic Perspective

A key issue of dynamic spectrum access in cognitive radio networks is to ensure that the interference incurred on primary users is under control. While interference models and optimization algorithms exist for spectrum sharing in cognitive radio networks, the study on network protocol design is still preliminary. In this paper, we aim to propose a distributed power control protocol for enabling effective spectrum sharing between primary and secondary users. The goal of power control is to maximize the aggregate capacity of the secondary network while ensuring that the cumulative interference incurred on primary users is within their interference temperature limit. We start by formulating the problem using network optimization, and then propose a distributed algorithm for solving the optimization problem using game theory. Based on the proposed distributed algorithm, we then design a network protocol for achieving distributed power control in cognitive radio networks. We find that while the network protocol can indeed achieve the desired performance of the power control game, it incurs significant protocol overheads during the convergence of the game. We therefore propose a hybrid protocol for better trade-offs between network optimality and protocol complexity. Evaluation results show the benefits of the proposed protocol for power control in cognitive radio networks.

Formulating and solving the femtocell deployment problem in two-tier heterogeneous networks

Recently, there has been an increasing interest in the deployment and management of femto base stations (BSs) to optimize the overall system performance in macro-femto heterogeneous networks. While deployment of femto BSs is typically not as planned as that of pico BSs, given a number of femto BSs to be distributed to candidate customer sites, questions regarding the optimal deployment locations and transmission configurations still need to be answered. In this paper, we formulate a joint optimization problem involving deployment location, cell selection, and power control to maximize the number of users that can be supported for a given number of femto BSs to be deployed in the macro cell. Since the formulated problem belongs to mixed-integer non-linear programming (MINLP), we propose an anytime algorithm that can yield a desirable solution within proper time limit. Specifically, based on the concept of coalition structure generation, the algorithm decouples the problem into the cluster formation sub-problem and power control sub-problem to find the optimal cluster head (femto BS location), cluster membership (cell selection), and transmission power in an iterative fashion. Evaluation results presented in this paper show that the proposed algorithm can effectively solve the problem with better complexity-optimality tradeoffs compared to baseline approaches.

Modeling and Comparison of Primary User Detection Techniques in Cognitive Radio Networks

In this paper, we investigate the problem of spectrum sensing in cognitive radio networks. Compared with related work that aims to propose techniques at different layers of the network protocol stack for detecting primary users, we aim to investigate the capabilities and limitations of different primary user detection techniques from the perspective of network optimization. The goal is to understand the fundamental performance tradeoffs of different primary user detection techniques without being limited by existing cognitive radio software and hardware platforms. To proceed, we first identify several dimensions for designing primary user detection techniques in cognitive radio networks, and then formulate primary user detection techniques using mixed- integer nonlinear programming (MINLP). Evaluation results show the benefits of using the proposed optimization framework for profiling the fundamental characteristics of primary user detection techniques.

Weakest-Link Coalition: Further Investigation on Cooperative Interference-Aware Spectrum Sensing and Access

Interference-aware spectrum sensing extends conventional interference-agnostic sensing by exploring the fact that missed detection does not necessarily result in outage or intolerable interference on the primary user. While related work has motivated and demonstrated the benefits of interference-aware spectrum sensing for spectrum hole discovery, the inherent conflict of interests among the set of cooperative users with interference-aware spectrum detectors has not been properly formulated and addressed. In this paper, we aim to bridge the gap by considering a coalition-based model, where the set of secondary users is to be partitioned into multiple coalitions for cooperative spectrum sensing and access. The goal is to maximize the utility sum of all secondary users while observing the protection requirement of the primary user. Since the user with the largest interference probability in a coalition critically limits the detection performance of the coalition, there is a trade-off in determining the optimal coalition structure in the network. To proceed, we first formulate a joint threshold detection and coalition formation problem under the target cooperative model, and then explore important properties of the target problem. Our proposed algorithms based on polyblock approximation and search space partition can effectively solve the formulated problem with significant performance gains and complexity reduction against baseline approaches proposed in related work.

Evolution of Cooperation: A Case with Interference-Aware Cooperative Spectrum Sensing in Cognitive Radio Networks

We consider in this work a group of secondary users with backlogged traffic to transmit in the primary network. To avoid interfering with the primary user, each secondary user must perform interference-aware spectrum sensing before transmission. Unlike conventional sensing techniques, interference-aware spectrum sensing allows a secondary user to adjust its sensing parameters for optimal performance depending on the probability of interfering with the primary user. While interference-aware sensing can achieve better performance for individual users, challenges arise when secondary users collaborate with each other for cooperative spectrum sensing due to their unequal interference probabilities that result in a conflict for setting the optimal sensing parameters. To model this problem, we consider an interference-aware cooperative sensing game and analyze player behaviors under such a game. We find that there is a unique pure Nash equilibrium of the game, but it tends to deviate from the desirable solution of social optimum. We then design a repeated game based on evolutionary game theory to address this problem. Players in the repeated game have the chance to revenge “uncooperative” players in ensuing repetitions for driving the equilibrium to the social optimum. We show through numerical results that the proposed game of evolution does achieve the desirable performance for interference-aware cooperative sensing in dynamic spectrum access.

Protection of the undetectables: A study on the primary receiver protection problem in cognitive radio networks

In this paper, we investigate the problem of primary receiver protection in a cell-based network after the presence of the primary transmitter has been detected by cognitive radio. Since the primary transmitter may unicast, multicast or broadcast data to receivers anywhere in the cell, our goal is to protect the entire cell so the received SINR anywhere in the cell is maintained above the target QoS constraint. We formulate the problem using network optimization, and investigate an iterative algorithm for solving the problem. A solution based on partial sampling of monitoring points in the view angles of individual secondary transmitters is then investigated. Numerical results show the benefits of the proposed solution.

Enhancing campus VoIP service for ubiquitous communication on dual-mode mobile handsets

In this paper, we consider a university campus that has an established infrastructure for supporting SIP-based VoIP service through the campus wireless data network. The campus WLAN, however, does not have 100% full coverage, and hence users cannot make untethered VoIP calls anywhere on campus. The goal of this paper is to overcome the limitations of such WLAN dead spots and improve user experience when making VoIP calls. Different from related work that relies on peer-to-peer communication for multi-hop relay, we propose an approach called ldquodual-mode communicationrdquo to leverage the availability of dual-mode handsets for ubiquitous communication on campus. We implement the proposed approach and evaluate its performance in the campus testbed environment. We find that an opportunistic usage of dual communication modes on mobile handsets does allow ubiquitous voice communication in WLAN dead spots. However, it has one problem as the potential lack of voice call continuity during hand-off between the two modes that can cause degradation of the speech quality. We adopt a cross-layer solution based on signal processing algorithms to address the problem, thus achieving seamless voice call continuity while enabling ubiquitous voice communication on campus. Testbed evaluations show promising results for future research along the proposed direction.

Power control refined: Addressing the problems in optimization-based distributed algorithms for opportunistic spectrum sharing

Transmission power control is one of the key enabling technologies in opportunistic spectrum sharing for secondary users to optimize their performance without incurring undesirable interference on primary users. Various optimization models and algorithms for different scenarios and design objectives have hence been proposed in related work. While ideally these algorithms can find optimal solutions for power control, in practice it is very likely that the output powers are suboptimal or even infeasible if these algorithms are applied in a distributed environment. The reasons are due to various practical considerations such as the overheads of power training, use of the control channel, and dynamics of primary user activity. To address the problem of unfit outputs thus obtained, we investigate in this paper low-complexity algorithms that can be used in tandem with these distributed algorithms by quickly adapting undesirable solutions for use by secondary users such that feasibility is restored and/or optimality is improved. Compared with the approach of finding a new solution based on linear approximation of the optimization problem, we show through evaluations that the proposed algorithm is simple yet effective in achieving the desired goal.