Haiyan Luo

Prediction-Based Spectrum Aggregation with Hardware Limitation in Cognitive Radio Networks

In cognitive radio networks, multiple spectrum opportunities can be used together to satisfy the service requirement by spectrum aggregation. In this paper, an admission control algorithm and a spectrum assignment strategy are proposed in order for both increasing the spectrum aggregation aware access capacity and decreasing the channel switch times when the channel states change. Considering different bandwidth requirement of secondary users, the proposed greedy admission algorithm takes limited aggregation capability into account. The channel switch times of secondary users at sensing moments is minimized based on the prediction of primary activities and the corresponding channel state transitions. The concept of outage probability is introduced into the scheme to indicate the probability of channel switch. The numerical results show the performance improvement of the proposed algorithms.

A Column Generation Approach for Spectrum Allocation in Cognitive Wireless Mesh Network

Cognitive radio (CR) has the potential to substantially improve the system capacity and adaptability of wireless mesh network (WMN). In this paper we investigate the achievable performance gain of cognitive wireless mesh network (CWMN), in which all nodes are equipped with CRs, by jointly optimizing spectrum allocation, routing and time scheduling. The formulated optimization problem aims to minimize the system activation time to satisfy the given traffic demands, under the constraint of multiple access interference and the limited available spectrum bands at each node. Then we develop a column generation (CG) approach to solve this problem. Our analytical model is validated by the simulation results, which provide a better performance compared with fixed bandwidth allocation.

Sensing error aware delay-optimal channel allocation scheme for cognitive radio networks

Spectrum sensing is not always perfect in practical cognitive radio networks. In this paper, two kinds of sensing errors are considered into the channel allocation scheme. Our work focuses on the cases that the channel availability varies fast during a channel allocation period, in which case the channel dynamics needs to be considered. The sensing errors are modeled to derive the metric of mean delay for each user-channel combination using the vacation queueing model. Further, the optimal resource allocation is determined based on the mean delay metric by bipartite graph matching. The simulation results indicate that the proposed mean delay metric can represent the transmission performance successfully, and the proposed resource allocation scheme is robust to sensing errors.

Optimal Resource Allocation for Cognitive Radio Networks with Imperfect Spectrum Sensing

In this paper, an optimal resource allocation scheme is proposed for multi-user multi-channel cognitive radio networks under imperfect spectrum sensing. The channel dynamic model and the sensing errors are considered together to derive the metric of mean delay for each user-channel combination based on the vacation queueing model. Finally, the optimal resource allocation is determined according to the average system delay by bipartite graph matching. The simulation results indicate that the proposed mean delay metric can represent the transmission performance successfully.

Uplink Scheduling for Cognitive Radio Cellular Network with Primary User's QoS Protection

In this paper, the problem of the multi-user uplink scheduling in cognitive radio cellular network (CogCell) is investigated. The objective is to maximize the system throughput, while protecting the QoS of primary user (PU) from being affected by secondary user (SU). Here, PUs QoS is represented by its signal-to-interference-plus-noise (SINR) outage probability. It is equivalent to say that SU can increase its transmit power to enhance the system performance as long as PUs SINR outage probability does not exceed the predefined threshold. So the first scheduling algorithm is proposed to maximize the system throughput through utilizing the multi-user diversity. Different from the first algorithm which does not take the fairness among SUs into account, the second scheduling algorithm with considering proportional fairness among SUs is proposed. It is shown to provide a satisfactory tradeoff between maximizing the system throughput and achieving fairness among SUs. Finally, these proposed algorithms are validated through extensive simulations.

Opportunistic cognitive relaying: a win-win spectrum sharing scheme

A cost-effective spectrum sharing architecture is proposed to enable the legacy noncognitive secondary system to coexist with the primary system. Specifically, we suggest to install a few intermediate nodes, namely, the cognitive relays, to conduct the spectrum sensing and coordinate the spectrum access. To achieve the goal of win-win between primary and secondary systems, the cognitive relay may act as a cooperator for both of them, and an Opportunistic Cognitive Relaying (OCR) scheme is specially devised. In this scheme, the cognitive relay opportunistically switches among three different working modes, that is, Relay for Primary Link (RPL), Relay for Secondary Link (RSL), or Relay for Neither of the Links (RNL), respectively, based on the channel-dependent observation of both systems. In addition, the transmit power for cognitive relay and secondary transmitter in each mode are optimally determined by maximizing the transmission rate of secondary system while keeping or even reducing the outage probability of primary system. Simulation results validate the efficiency of the proposed spectrum sharing scheme.

Cognitive cooperative relaying

Previous works about spectrum sharing in licensed band are all based on a default assumption that the secondary users are equipped with cognitive radios, which enable them to accomplish the spectrum sensing and the ensuing spectrum access. Unfortunately, current wireless communication devices generally lack any functionality of cognition. It is rather challenging to enable such wireless devices to share spectrum with licensed primary systems. As a promising solution, in this paper, we propose a scheme called cognitive cooperative relaying, which introduces a kind of intermediate node, i.e., the cognitive relay, who senses the spectrum activity instead of the secondary user and then opportunistically relays the primary or secondary signal so that the transmission rate of the primary link will keep constant, while that of the secondary link will be maximized. The key feature of the proposed scheme is that, the cognitive relay serves as not only an opportunistic relay for either the primary or secondary transmission pair, but also the Spectrum Policy Server. Simulation results show that, in terms of achievable rate of the secondary user, the proposed spectrum sharing scheme significantly outperforms the conventional one where the secondary user is configured with cognitive radio, which validates a new way of spectrum sharing for current wireless system.

Cognitive Radio Transmission Strategies Exploiting the Primary-Link Adaptivity

This paper aims at maximizing the average spectral efficiency of a secondary link in a cognitive radio context, where both the primary and secondary users are equipped with the adaptive modulation and coding (AMC) capability. In the training phase, the fixed training power of the secondary user is selected such that the prescribed average spectral efficiency of the primary link is guaranteed. In the data transmission phase, the transmit power and the AMC mode of the secondary user are selected under the maximum packet error rate (PER) constraint of the primary user, as well as the average power and PER constraints of the secondary user. According to different kinds of primary-link information available to the secondary user, i.e., the transmission mode, the signal-to-interference-plus-noise ratio (SINR), and no information at all, three optimization problems that maximize the average spectral efficiency of the secondary user are formulated, respectively. Based on their optimal solutions, three AMC-based adaptive transmission strategies that are composed of both online and offline algorithms are proposed. Their performances are then evaluated by extensive simulation.

Performance Comparison of IEEE 802.16e and IEEE 802.20 Systems under Different Frequency Reuse Schemes

IEEE 802.16e and 802.20 are emerging as two promising technologies for broadband wireless access systems. In order to improve capacity and coverage performance, both of them addressed a fractional frequency reuse (FFR) scheme to combat co-channel interference in multi-cell deployment, which is referred to as FFR16 and FFR20 respectively in this paper. As for the scheme of FFR20, virtual area partition is proposed in this paper, and fractional frequency reuse factor (FFRF) is achieved by tuning the parameter of signal strength ratio. The optimal combination of resource allocation strategy and signal strength ratio is determined through simulation. In order to compare the performance of FFR16 and FFR20, three evaluation metrics are introduced, including average throughput, outage probability and spectrum efficiency. Simulation results show that outage probability is much lower under FFR20 scheme, which goes beyond the acceptable range when FFRF is smaller than 2.4. The resource utilization efficiencies of both are continuously increasing with regard to FFRF within range [2.4, 3]. Besides, FFR20 outperforms FFR16 under given conditions, in terms of average throughput and spectrum efficiency.

Optimal Bit and Power Allocation in Broadband Cognitive Radio System

In this paper, we study the problem of bit and power allocation in broadband cognitive radio system. In the broadband communication system, the primary transmitter employs Orthogonal Frequency Division Multiplexing (OFDM) technique on the whole bandwidth. A cognitive user, which has the ability of detecting the transmission of the primary link on each subcarrier, attempts to use the same bandwidth. The goal of this paper is to study how to optimally allocate bit and power on each subcarrier at the cognitive transmitter so that the sum-rate of the cognitive user is maximized under the condition that the primary transmission is not affected. Based on the framework presented by A. Jovicic and P. Viswanath, we first formulate the problem into an optimization problem with integer variables and then propose a greedy bit and power allocation algorithm. We also prove that the proposed algorithm is the optimal solution to the optimization problem.