Throughput analysis for cognitive radio networks with multiple primary users and imperfect spectrum sensing

In cognitive radio networks, the licensed frequency bands of the primary users (PUs) are available to the secondary user (SU) provided that they do not cause significant interference to the PUs. In this study, the authors analysed the normalised throughput of the SU with multiple PUs coexisting under any frequency division multiple access communication protocol. The authors consider a cognitive radio transmission where the frame structure consists of sensing and data transmission slots. In order to achieve the maximum normalised throughput of the SU and control the interference level to the legal PUs, the optimal frame length of the SU is found via simulation. In this context, a new analytical formula has been expressed for the achievable normalised throughput of SU with multiple PUs under prefect and imperfect spectrum sensing scenarios. Moreover, the impact of imperfect sensing, variable frame length of SU and the variable PU traffic loads, on the normalised throughput has been critically investigated. It has been shown that the analytical and simulation results are in perfect agreement. The authors analytical results are much useful to determine how to select the frame duration length subject to the parameters of cognitive radio network, such as network traffic load, achievable sensing accuracy and number of coexisting PUs

Cognitive MAC protocols for mobile Ad-Hoc networks

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.The term of Cognitive Radio (CR) used to indicate that spectrum radio could be accessed dynamically and opportunistically by unlicensed users. In CR Networks, Interference between nodes, hidden terminal problem, and spectrum sensing errors are big issues to be widely discussed in the research field nowadays. To improve the performance of such kind of networks, this thesis proposes Cognitive Medium Access Control (MAC) protocols for Mobile Ad-Hoc Networks (MANETs). From the concept of CR, this thesis has been able to develop a cognitive MAC framework in which a cognitive process consisting of cognitive elements is considered, which can make efficient decisions to optimise the CR network. In this context, three different scenarios to maximize the secondary user's throughput have been proposed. We found that the throughput improvement depends on the transition probabilities. However, considering the past information state of the spectrum can dramatically increases the secondary user's throughput by up to 40%. Moreover, by increasing the number of channels, the throughput of the network can be improved about 25%. Furthermore, to study the impact of Physical (PHY) Layer errors on cognitive MAC layer in MANETs, in this thesis, a Sensing Error-Aware MAC protocols for MANETs has been proposed. The developed model has been able to improve the MAC layer performance under the challenge of sensing errors. In this context, the proposed model examined two sensing error probabilities: the false alarm probability and the missed detection probability. The simulation results have shown that both probabilities could be adapted to maintain the false alarm probability at certain values to achieve good results. Finally, in this thesis, a cooperative sensing scheme with interference mitigation for Cognitive Wireless Mesh Networks (CogMesh) has been proposed. Moreover, a prioritybased traffic scenario to analyze the problem of packet delay and a novel technique for dynamic channel allocation in CogMesh is presented. Considering each channel in the system as a sub-server, the average delay of the users' packets is reduced and the cooperative sensing scenario dramatically increases the network throughput 50% more as the number of arrival rate is increased

A Unified Approach to Optimal Opportunistic Spectrum Access under Collision Probability Constraint in Cognitive Radio Systems

We consider a cognitive radio system with one primary channel and one secondary user, and then we introduce a channel-usage pattern model and a fundamental access scheme in this system. Based on this model and fundamental access scheme, we study optimal opportunistic spectrum access problem and formulate it as an optimization problem that the secondary user maximizes spectrum holes utilization under the constraint of collision tolerable level. And then we propose a unified approach to solve this optimization problem. According to the solution of the optimization problem, we analyze and present optimal opportunistic spectrum access algorithms in several cases that the idle period follows uniform distribution, exponential distribution, and Pareto or generalized Pareto distribution. Theoretical analysis and simulation results both show that the optimal opportunistic spectrum access algorithms can maximize spectrum holes utilization under the constraint that the collision probability is bounded below collision tolerable level. The impact of sensing error is also analyzed by simulation

逐次干渉除去を用いた多元接続システムのパワー割り当てに関する研究

In future wireless communication networks, the number of devices is likely to increase dramatically due to potential development of new applications such as the Internet of Things (IoT). Consequently, radio access network is required to support multiple access of massive users and achieve high spectral efficiency. From the information theoretic perspective, orthogonal multiple access protocols are suboptimal. To achieve the multiple access capacity, non-orthogonal multiple access protocols and multiuser detection (MUD) are required. For the non-orthogonal code-division multiple access (CDMA), several MUD techniques have been proposed to improve the spectrum efficiency. Successive interference cancellation (SIC) is a promising MUD techniques due to its low complexity and good decoding performance. Random access protocols are designed for the system with bursty traffic to reduce the delay, compared to the channelized multiple access. Since the users contend for the channel instead of being assigned by the base station (BS), collisions happen with a certain probability. If the traffic load becomes relatively high, the throughput of these schemes steeply falls down because of collisions. However, it has been well-recognized that more complex procedures can permit decoding of interfering signals, which is referred to as multi-packet reception (MPR). Also, an SIC decoder might decode more packets by successively subtracting the correctly decoded packets from the collision. Cognitive radio (CR) is an emerging technology to solve the problem of spectrum scarcity by dynamically sharing the spectrum. In the CR networks, the secondary users (SUs) are allowed to dynamically share the frequency bands with primary users (PUs) under primary quality-of-service (QoS) protection such as the constraint of interference temperature at the primary base station (PBS). For the uplink multiple access to the secondary base station (SBS), transmit power allocation for the SUs is critical to control the interference temperature at the PBS. Transmit power allocation has been extensively studied in various multiple access scenarios. The power allocation algorithms can be classified into two types, depending on whether the process is controlled by the base station (BS). For the centralized power allocation (CPA) algorithms, the BS allocates the transmit powers to the users through the downlink channels. For the random access protocols, there are also efforts on decentralized power allocation (DPA) that the users select transmit powers according to given distributions of power and probability, instead of being assigned the transmit power at each time slot by the BS. In this dissertation, the DPA algorithms for the random access protocols with SIC are investigated and new methods are proposed. First a decentralized multilevel power allocation algorithm to improve the MAC throughput performance is proposed, for the general SIC receiver that can decode multiple packets from one collision. Then an improved DPA algorithm to maximize the overall system sum rate is proposed, taking into account of both the MAC layer and PHY layer. Finally, a DPA algorithm for the CR secondary random access is proposed, considering the constraint of interference temperature and the practical assumption of imperfect cancellation. An opportunistic transmission protocol for the fading environment to further reduce the interference temperature is also proposed. For the future work, the optimal DPA for the random access with the SIC receiver is still an open problem. Besides, advanced multiple access schemes that aim to approach the multiple access capacity by combining the advantages of the network coded cooperation, the repetition slotted ALOHA, and the SIC receiver are also interesting.電気通信大学201

Practical Spectrum Aggregation for Secondary Networks with Imperfect Sensing

We investigate a collision-sensitive secondary network that intends to opportunistically aggregate and utilize spectrum of a primary network to achieve higher data rates. In opportunistic spectrum access with imperfect sensing of idle primary spectrum, secondary transmission can collide with primary transmission. When the secondary network aggregates more channels in the presence of the imperfect sensing, collisions could occur more often, limiting the performance obtained by spectrum aggregation. In this context, we aim to address a fundamental query, that is, how much spectrum aggregation is worthy with imperfect sensing. For collision occurrence, we focus on two different types of collision: one is imposed by asynchronous transmission; and the other by imperfect spectrum sensing. The collision probability expression has been derived in closed-form with various secondary network parameters: primary traffic load, secondary user transmission parameters, spectrum sensing errors, and the number of aggregated sub-channels. In addition, the impact of spectrum aggregation on data rate is analysed under the constraint of collision probability. Then, we solve an optimal spectrum aggregation problem and propose the dynamic spectrum aggregation approach to increase the data rate subject to practical collision constraints. Our simulation results show clearly that the proposed approach outperforms the benchmark that passively aggregates sub-channels with lack of collision awareness

Practical Spectrum Aggregation for Secondary Networks with Imperfect Sensing

We investigate a collision-sensitive secondary network that intends to opportunistically aggregate and utilize spectrum of a primary network to achieve higher data rates. In opportunistic spectrum access with imperfect sensing of idle primary spectrum, secondary transmission can collide with primary transmission. When the secondary network aggregates more channels in the presence of the imperfect sensing, collisions could occur more often, limiting the performance obtained by spectrum aggregation. In this context, we aim to address a fundamental query, that is, how much spectrum aggregation is worthy with imperfect sensing. For collision occurrence, we focus on two different types of collision: one is imposed by asynchronous transmission; and the other by imperfect spectrum sensing. The collision probability expression has been derived in closed-form with various secondary network parameters: primary traffic load, secondary user transmission parameters, spectrum sensing errors, and the number of aggregated sub-channels. In addition, the impact of spectrum aggregation on data rate is analysed under the constraint of collision probability. Then, we solve an optimal spectrum aggregation problem and propose the dynamic spectrum aggregation approach to increase the data rate subject to practical collision constraints. Our simulation results show clearly that the proposed approach outperforms the benchmark that passively aggregates sub-channels with lack of collision awareness