Optimal Power Allocation for Multiuser Underlay Cognitive Radio Networks under QoS and Interference Temperature Constraints

Power allocation is an important issue for Cognitive Radio Networks(CRNs),since it needs to consider the Quality of Service(QoS) for Secondary Users(SUs) while maintaining the interference power to Primary User(PU) below the Interference Temperature(IT) threshold. In this paper, based on Euclidean projection, we propose a distributed power control algorithm with QoS requirements to minimise the total power consumption of SUs under the time-varying channel scenario. Considering the maximum transmit power constraints and the minimum signal to interference plus noise constraints for each SU, together with the IT constraints for each PU, the power allocation problem is transformed into a convex optimization problem without auxiliary variables, and is solved by the Lagrangian dual method with less information exchange.Simulation results demonstrate that the proposed scheme is superior to the Iterative Water-Filling Algorithm(IWFA).

Joint Optimal Sensing Threshold and Subcarrier Power Allocation in Wideband Cognitive Radio for Minimising Interference to Primary User

Cognitive Radio （CR） can use the fre- quency band allocated to a Primary User （PU） on the premise that it will prevent significant of avoiding causing great interference to the PU. In this paper, we consider a wideband CR system where the Secondary User （SU） mini- raises its interference to the PU by jointly al- locating the optimal sensing threshold and sub- carrier power. A multi-parameter optimization problem is formulated to obtain the joint opt- imal allocation by alternating direction opti- mization, which minimises the total interfer- ence to the PU over all of the subcarriers sub- ject to the constraints on the throughput, Bit Error Rate （BER） and maximal total power of the SU, the subcarrier rate and interference power of the PU, and the false alarm and mis- detection probabilities of each subcarrier. The simulation results show that the proposed joint allocation algorithm can achieve the desired mitigation on the interference to the PU at the different subcarrier gains.

A New Power Allocation Algorithm in Cognitive Radio Networks

Most resource allocation algorithms are based on interference power constraint in cognitive radio networks.Instead of using conventional primary user interference constraint,we give a new criterion called allowable signal to interference plus noise ratio(SINR) loss constraint in cognitive transmission to protect primary users.Considering power allocation problem for cognitive users over flat fading channels,in order to maximize throughput of cognitive users subject to the allowable SINR loss constraint and maximum transmit power for each cognitive user,we propose a new power allocation algorithm.The comparison of computer simulation between our proposed algorithm and the algorithm based on interference power constraint is provided to show that it gets more throughput and provides stability to cognitive radio networks.

A Robust Energy Efficiency Power AllocationAlgorithm in Cognitive Radio Networks

In order to solve the problem that traditional energy efficiency power allocation algorithms usually require the assumption of constant or perfect channel state information in cognitive radio networks(CRNs),which may lead to performance degradation in real systems with disturbances or uncertainties,we propose a robust energy efficiency power allocation algorithm for underlay cognitive radio(CR)systems with channel uncertainty in consideration of interference power threshold constraint and minimum target SINR requirement constraint.The ellipsoid sets are used to describe the channel uncertainty,and a constrained fractional programming for the allocation is transformed to a convex optimization problem by worst-case optimization approach.A simplified version of robust energy efficiency scheme by a substitutional constraint having lower complexity is presented.Simulation results show that our proposed scheme can provide higher energy efficiency compared with capacity maximization algorithm and guarantee the signal to interference plus noise ratio(SINR)requirement of each cognitive user under channel uncertainty.

OPTIMAL POWER ALLOCATION FOR COGNITIVE RADIO UNDER INTERFERENCE OUTAGE CONSTRAINT

Cognitive radio is able to share the spectrum with primary licensed user,which greatly improves the spectrum efficiency.We study the optimal power allocation for cognitive radio to maximize its ergodic capacity under interference outage constraint.An optimal power allocation scheme for the secondary user with complete channel state information is proposed and its approxi-mation is presented in closed form in Rayleigh fading channels.When the complete channel state in-formation is not available,a more practical transmitter-side joint access ratio and transmit power constraint is proposed.The new constraint guarantees the same impact on interference outage prob-ability at primary user receiver.Both the optimal power allocation and transmit rate under the new constraint are presented in closed form.Simulation results evaluate the performance of proposed power allocation schemes and verify our analysis.

Game Theoretic Analysis of Joint Rate and Power Allocation in Cognitive Radio Networks

Spectrum sharing is an essential enabling functionality to allow the coexistence between primary user (PU) and cognitive users (CUs) in the same frequency band. In this paper, we consider joint rate and power allocation in cognitive radio networks by using game theory. The optimum rates and powers are obtained by iteratively maximizing each CU’s utility function, which is designed to guarantee the protection of primary user (PU) as well as the quality of service (QoS) of CUs. In addition, transmission rates of some CUs should be adjusted if corresponding actual signal-to-interference-plus-noise ratio (SINR) falls below the target SINR. Based on the modified transmission rate for each CU, distributed power allocation is introduced to further reduce the total power consumption. Simulation results are provided to demonstrate that the proposed algorithm achieves a significant gain in power saving.

Joint Adaptive Modulation and Power Allocation in Cognitive Radio Networks

Link adaptation is an important issue in the design of cognitive radio networks, which aims at making efficient use of system resources. In this paper, we propose and investigate a joint adaptive modulation and power allocation algorithm in cognitive radio networks. Specifically, the modulation scheme and transmit power are adjusted adaptively according to channel conditions, interference limit and target signal-to-interference-plus-noise ratio (SINR). As such the total power consumption of cognitive users (CUs) is minimized while keeping both the target SINR of CUs and interference to primary user (PU) at an acceptable level. Simulation results are provided to show that the proposed algorithm achieves a significant gain in power saving.

Relay Selection and Power Allocation in Amplify-and-Forward Cognitive Radio Systems Based on Spectrum Sharing

In this paper, we consider a spectrum sharing scheme that is a joint optimization of relay selection and power allocation at the secondary transmitter, which aims to achieve the maximum possible throughput for the secondary user. This paper considers the scenario where the primary user is incapable of supporting its target signal-to-noise ratio (SNR). More especially, the secondary transmitter tries to assist the primary user with achieving its target SNR by cooperative amplify-and-forward (AF) relaying with two-phase. By exhaustive search for all candidate secondary transmitters, an optimal secondary transmitter can be selected, which not only can satisfy the primary user’s target SNR, but also maximize the secondary user’s throughput. The optimal secondary transmitter acts as a relay for the primary user by allocating a part of its power to amplify-and-forward the primary signal over the primary user’s licensed spectrum bands. At the same time, as a reward, the optimal secondary transmitter uses the remaining power to transmit its own signal over the remaining licensed spectrum bands. Thus, the secondary user obtains the spectrum access opportunities. Besides, there is no interference between the primary user and the secondary user. We study the joint optimization of relay selection and power allocation such that the secondary user’s throughput is maximized on the condition that it satisfies the primary user’s target SNR. From the simulation, it is shown that the joint optimization of relay selection and power allocation provides a significant throughput gain compared with random relay selection with optimal power allocation (OPA) and random relay selection with water-filling power allocation (WPA). Moreover, the simulation results also shown that our spectrum sharing scheme obtains the win-win solution for the primary system and the secondary system.

Full-Filling Subcarrier Power Allocation in OFDMA-Based Cognitive Radio Systems

When implementing an appropriate windowing, the interference from a Cognitive Radio (CR) system to licensed systems (primary users) will be significantly reduced. Consequently, power allocated to subcarriers can be increased, especially subcarriers having far spectral distance to primary user bands can be allocated full of its maximum possible power. In this paper, we propose a new class of sub-optimal subcarrier power allocation algorithm that significantly reduces complexity of OFDMA-based CR systems. Two sub-optimal proposals, called Pre-set Filling Range (PFR) and Maximum Filling Range (MFR) are studied. Investigations show that this new power allocating algorithm allows CR systems obtain high throughput while retaining low complexity.

A NOVEL PAPR REDUCTION WITH TRELLIS SHAPING FOR NC-OFDM IN COGNITIVE RADIO

In this paper, trellis shaping is applied to reducing the Peak-to-Average Power Ratio(PAPR) of NC-OFDM signals due to the fact that the total number of active subcarriers and their locations might change continuously in a dynamic spectrum access network.A new branch metric of trellis shaping is proposed which reduces the PAPR of OFDM signals through minimizing the variance of the power by VA decoder.The overall performance considerably depends on the type of signal mapping, and therefore a new type of 64QAM mapping method is designed.Simulation results show that this scheme significantly reduces the PAPR.Finally, a significant phenomenon is demonstrated that the PAPR of NC-OFDM signals in which the deactivated carriers is distributed in the Bernoulli distribution has better performance than that of OFDM signals.

Power Allocation for Cooperative Communications in Non-Orthogonal Cognitive Radio Vehicular Ad-Hoc Networks

To achieve the better system performance for cooperative communication in non-orthogonal cognitive radio vehicular adhoc networks(CR-VANETs),this paper investigates the power allocation considering the interference to the main system in a controllable range.We propose a three-slot one-way vehicle system model where the mobile vehicle nodes complete information interaction with the assistance of other independent nodes by borrowing the unused radio spectrum with the primary networks.The end-to-end SNR relationship in overlay and underlay cognitive communication system mode are analyzed by using two forwarding protocol,namely,decode-and-forward(DF)protocol and amplify-and-forward(AF)protocol,respectively.The system outage probability is derived and the optimal power allocation factor is obtained via seeking the minimum value of the approximation of system outage probability.The analytical results have been confirmed by means of Monte Carlo simulations.Simulation results show that the proposed system performance in terms of outage under the optimal power allocation is superior to that under the average power allocation,and is also better than that under other power allocation systems.

Power Allocation for Sensing-Based Spectrum Sharing Cognitive Radio System with Primary Quantized Side Information

Spectrum access approach and power allocation scheme are important techniques in cognitive radio(CR) system,which not only affect communication performance of CR user(secondary user,SU) but also play decisive role for protection of primary user(PU).In this study,we propose a power allocation scheme for SU based on the status sensing of PU in a single-input single-output(SISO) CR network.Instead of the conventional binary primary transmit power strategy,namely the sensed PU has only present or absent status,we consider a more practical scenario when PU transmits with multiple levels of power and quantized side information known by SU in advance as a primary quantized codebook.The secondary power allocation scheme to maximize the average throughput under the rate loss constraint(RLC) of PU is parameterized by the sensing results for PU,the primary quantized codebook and the channel state information(CSI) of SU.Furthermore,Differential Evolution(DE) algorithm is used to solve this non-convex power allocation problem.Simulation results show the performance and effectiveness of our proposed scheme under more practical communication conditions.

Joint channel allocation and power control with fairness in multi-hop cognitive radio networks

This paper investigates channel allocation and cognitive radio networks. The color-sensitive graph power control schemes in OFDM-based multi-hop coloring （CSGC） model is viewed as an efficient solution to the spectrum assignment problem. The model is extended to combine with the power con- trol strategy to avoid interference among secondary users and adapt dynamic topology. The optimiza- tion problem is formulated encompassing the channel allocation and power control with the interfer- ence constrained below a tolerable limit. Meanwhile, the proposed resource allocation scheme takes the fairness of secondary users into account in obtaining the solution of optimization. Numerical re- suits show that the proposed strategy outperforms the existing spectrum assignment algorithms on the performance of both the network throughput and minimum route bandwidth of all routes, as well as the number of connected multi-hop routes which implies the fairness among secondary users.

Power Allocation in Primary User-Assisted Multi-Channel Cognitive Radio Networks

This paper addresses power allocation problem for spectrum sharing multi-band cognitive radio networks, where the primary user (PU) allows secondary users (SUs) to transmit simultaneously with it by coding SU's signal together with its own signal. The PU acts as the relay for the SUs and sells its transmit power to the SUs to increase its benefit, and the SUs bid for the PU's transmit power for maximizing their utilities. We propose a power allocation scheme based on traditional ascending clock auction, in which the SUs iteratively submit the optimal power demand to the PU according to the PU's announced price, and the PU updates that price based on all SUs' total power demands. Then we mathematically prove the convergence property of the proposed auction algorithm (i.e., the auction algorithm converges in a finite number of clocks), and show that the proposed power auction algorithm can maximize the social welfare. Finally, the performance of the proposed scheme is verified by the simulation results.

Joint channel and power allocation scheme for cognitive wireless networks

Cognitive radio （CR） is a promising technology deemed to improve the efficiency of spectrum utilization. This paper considers a spectrum underlay cognitive radio network, in which the cognitive users （CUs） are allowed to use the radio spectrum concurrently with the primary users （PUs） under the interference temperature constraint. We investigate the system performance by using the proposed joint channel and power allocation scheme under two transmit strategies to achieve higher data rates and performance diversity gain respectively. Simulation results show that the proposed scheme provides a significant improvement on the bit error rate （BER） performance and spectrum efficiency of a cognitive wireless network.

LOW-COMPLEXITY JOINT BEAMFORMING AND POWER ALLOCA-TION FOR SINR BALANCING IN COGNITIVE RADIO NETWORKS

We consider the Signal-to-Interference plus Noise Ratio(SINR) balancing problem in-volving joint beamfoming and power allocation in the Cognitive Radio(CR) network,wherein the Single-Input Multi-Output Multiple Access Channels(SIMO-MAC) are assumed.Subject to two sets of constraints:the interference temperature constraints of Primary Users(PUs) and the peak power constraints of Cognitive Users(CUs),a low-complexity joint beamforming and power allocation algo-rithm called Semi-Decoupled Multi-Constraint Power Allocation with Constraints Preselection(SDMCPA-CP) for SINR balancing is proposed.Compared with the existing algorithm,the proposed SDMCPA-CP can reduce the number of matrix inversions and matrix eigen decompositions signifi-cantly,especially when large numbers of PUs and CUs are active,while still providing the optimal balanced SINR level for all the CUs.

Research on User Pairing Techniques Based on NOMA in Cognitive Radio Networks

This paper outlined a Non-Orthogonal Multiple Access (NOMA) grouping transmission scheme for cognitive radio networks. To address the problems of small channel gain difference of the middle part users caused by the traditional far-near pairing algorithm, and the low transmission rate of the traditional Orthogonal Multiple Access (OMA) transmission, a joint pairing algorithm was proposed, which provided multiple pairing schemes according to the actual scene. Firstly, the secondary users were sorted according to their channel gain, and then different secondary user groups were divided, and the far-near pairing combined with (Uniform Channel Gain Difference (UCGD) algorithm was used to group the secondary users. After completing the user pairing, the power allocation problem was solved. Finally, the simulation data results showed that the proposed algorithm can effectively improve the system transmission rate.

Optimal power allocation for multi-user OFDM and distributed antenna cognitive radio with RoF

In cognitive radio （CR）,power allocation plays an important role in protecting primary user from disturbance of secondary user. Some existing studies about power allocation in CR utilize ＇interference temperature＇ to achieve this protection,which might not be suitable for the OFDM-based CR. Thus in this paper,power allocation problem in multi-user orthogonal frequency division multiplexing （OFDM） and distributed antenna cognitive radio with radio over fiber （RoF） is firstly modeled as an optimization problem,where the limitation on secondary user is not ＇interference temperature＇,but that total throughput of primary user in all the resource units （RUs） must be beyond the given threshold. Moreover,based on the theorem about maximizing the total throughput of secondary user,equal power allocation algorithm is introduced. Furthermore,as the optimization problem for power allocation is not convex,it is transformed to be a convex one with geometric programming,where the solution can be obtained using duality and Karush-Kuhn-Tucker （KKT） conditions to form the optimal power allocation algorithm. Finally,extensive simulation results illustrate the significant performance improvement of the optimal algorithm compared to the existing algorithm and equal power allocation algorithm.

A Distributed Power Allocation Scheme in Green Cognitive Radio Ad Hoc Networks

For the realization of green communications in cognitive radio ad hoc networks(CRAHNs), selfadaptive and efficient power allocation for secondary users(SUs) is essential. With the distributed and timevarying network topology, it needs to consider how to optimize the throughput and power consuming, avoid the interference to primary users(PUs) and other SUs, and pay attention to the convergence and fairness of the algorithm. In this study, this problem is modeled as a constraint optimization problem. Each SU would adjust its power and corresponding strategy with the goal of maximizing its throughput. By studying the interactions between SUs in power allocation and strategy selection, we introduce best-response dynamics game theory and prove the existence of Nash equilibrium(NE) point for performance analysis. We further design a fully distributed algorithm to make the SUs formulate their strategy based on their utility functions, the strategy and number of neighbors in local area. Compared with the water-filling(WF) algorithm, the proposed scheme can significantly increase convergent speed and average throughput, and decrease the power consuming of SUs.

AN EFFECTIVE SUBOPTIMAL POWER LOADING SCHEME IN OFDM-BASED COGNITIVE RADIO SYSTEMS

Orthogonal frequency division multiplexing(OFDM) is an attractive modulation candidate for Cognitive Radio(CR) networks.Effective and reliable subcarrier power allocation in OFDM-based Cognitive Radio(CR) networks is a challenging problem.This paper focuses on the power allocation for OFDM-based Cognitive Radio(CR) networks.Our objective is to maximize the total transmission rates of Secondary Users(SU) by adjusting the power of subcarrier while the interference introduced to the Primary User(PU) is within a certain range and the total power of subcarrier is not beyond the total power constraint.We investigate the optimal power allocation algorithm for OFDM-based Cog-nitive Radio(CR) based on convex optimization theory.Then,because of high complexity of the op-timal power allocation algorithm,we propose an effective suboptimal power loading scheme.Theory analysis and simulation results show that the performance of the suboptimal power allocation algorithm is close to the performance of the optimal power allocation algorithm,while the complexity of the suboptimal power allocation algorithm is much lower.