Joint rate and power allocation for cognitive radios in dynamic spectrum access environment (original) (raw)
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the present study attempted to investigate the resource management in spectrum sharing cognitive radio networks where the transmit power and modulation level of secondary users (SUs) are adapted using iterative Foschini- Miljanic algorithm. We assumed that the SUs and primary user (PU) could use the same spectrum band, simultaneous to that of originally allocated to PU. The aim was to investigate the problem of minimizing the overall transmission power of SUs, while keeping the probabilistic interference and power budget below the specified thresholds. The main advantage of using probabilistic interference constraint is that it does not require the instantaneous feedback channel between SU transmitters (SUTs) and PU receiver (PUR). Furthermore, allocated power to SUs was first calculated using mentioned algorithm. Second, the signal to noise ratio (SNR) for all SUs was calculated based on allocated power and channel fading gains and then modulation level can be obtained based on calculated SNR and target bit error rate (BER). Numerical and comparison results representing the efficiency of the proposed network are also provided
Interference Management in Dynamic Spectrum Sharing Cognitive Radio
Cognitive radio is an exciting and new way of thinking and researching about wireless Communications. Indeed, it is already being considered as one of the key candidate technologies for the fourth-generation (4G) wireless systems. There are several drivers for the development of cognitive radio. Perhaps the most pressing of them is improved utilization of the electromagnetic radio spectrum: a highly valuable natural resource. Careful studies of the current usage of the radio spectrum by several agencies have already revealed that a large fraction of the radio spectrum is inadequately utilized. This basic finding has led to numerous research initiatives. Cognitive radios that are employed in a network with dynamic frequency assignments must operate efficiently in the presence of uncertainties and variations in the propagation characteristics of the network's communication links. One fundamental challenge is to ensure the quality of service (QoS) of the primary link while maximizing the transmission rate of the secondary links. Cognitive radio is an advanced technology for more efficient spectrum utilization systems based on opportunistic spectrum sharing and spectrum security, which finds white spaces and apply policies to determine when and in which bands they may communicate.
QoS-Aware Spectrum Sharing in Cognitive Wireless Networks
IEEE GLOBECOM 2007-2007 IEEE Global Telecommunications Conference, 2007
We consider QoS-aware spectrum sharing in cognitive wireless networks where secondary users are allowed to access the spectrum owned by a primary network provider. The interference from secondary users to primary users is constrained to be below the tolerable limit. Also, signal to interference plus noise ratio (SINR) of each secondary user is maintained higher than a desired level for QoS insurance. When network load is high, admission control needs to be performed to satisfy both QoS and interference constraints. We propose an admission control algorithm which is performed jointly with power control such that QoS requirements of all admitted secondary users are satisfied while keeping the interference to primary users below the tolerable limit. When all secondary users can be supported at minimum rates, we allow them to increase their transmission rates and share the spectrum in a fair manner. We formulate the joint power/rate allocation with max-min fairness criterion as an optimization problem. We show how to transform it into a convex optimization problem so that its globally optimal solution can be obtained. Numerical results show that the proposed admission control algorithm achieves performance very close to the optimal solution. Also, impacts of different system and QoS parameters on the network performance are investigated for both admission control and rate/power allocation problems.
Resource allocation for spectrum underlay in cognitive radio networks
IEEE Transactions on Wireless Communications, 2000
A resource allocation framework is presented for spectrum underlay in cognitive radio networks. We consider both interference constraints for primary users and quality of service (QoS) constraints for secondary users. Specifically, interference from secondary users to primary users is constrained to be below a tolerable limit. Also, signal to interference plus noise ratio (SINR) of each secondary user is maintained higher than a desired level for QoS insurance. We propose admission control algorithms to be used during high network load conditions which are performed jointly with power control so that QoS requirements of all admitted secondary users are satisfied while keeping the interference to primary users below the tolerable limit. If all secondary users can be supported at minimum rates, we allow them to increase their transmission rates and share the spectrum in a fair manner. We formulate the joint power/rate allocation with proportional and max-min fairness criteria as optimization problems. We show how to transform these optimization problems into a convex form so that their globally optimal solutions can be obtained. Numerical results show that the proposed admission control algorithms achieve performance very close to that of the optimal solution. Also, impacts of different system and QoS parameters on the network performance are investigated for the admission control, and rate/power allocation algorithms under different fairness criteria.
Power Control and Channel Allocation in Cognitive Radio Networks with Primary Users' Cooperation
IEEE Transactions on Mobile Computing, 2010
We consider a point-to-multipoint cognitive radio network that shares a set of channels with a primary network. Within the cognitive radio network, a base station controls and supports a set of fixed-location wireless subscribers. The objective is to maximize the throughput of the cognitive network while not affecting the performance of primary users. Both downlink and uplink transmission scenarios in the cognitive network are considered. For both scenarios, we propose two-phase mixed distributed/centralized control algorithms that require minimal cooperation between cognitive and primary devices. In the first phase, a distributed power updating process is employed at the cognitive and primary nodes to maximize the coverage of the cognitive network while always maintaining the constrained signal to interference plus noise ratio of primary transmissions. In the second phase, centralized channel assignment is carried out within the cognitive network to maximize its throughput. Numerical results are obtained for the behaviors and performance of our proposed algorithms. Index Terms-Wireless communications, dynamic spectrum access, distributed control, joint power control and channel allocation.
QoS constrained resource allocation to secondary users in cognitive radio networks
Computer Communications, 2009
In this paper, we consider a multi-channel cognitive radio network (CRN) where multiple secondary users share a single channel and multiple channels are simultaneously used by a single secondary user (SU) to satisfy their rate requirements. In such an environment, we attempt to evaluate the optimal power and rate distribution choices that each secondary user has to make in order to maintain their quality of service (QoS). Our measures for QoS include signal to interference plus noise ratio (SINR)/bit error rate (BER) and minimum rate requirement. We propose two centralized optimization frameworks in order to solve for the optimal resource management strategies. In the first framework, we determine the minimum transmit power that SUs should employ in order to maintain a certain SINR and use that result to calculate the optimal rate allocation strategy across channels. In the second framework, both transmit power and rate per channel are simultaneously optimized with the help of a bi-objective problem formulation. Unlike prior efforts, we transform the BER constraint into a convex constraint in order to guarantee optimality of the resulting solutions. Simulation results demonstrate that in both frameworks, optimal transmit power follows ''reverse water filling" process and rate allocation follows SINR. We also observe that, due to the ability to adapt both power and rate simultaneously to attain a certain BER, the joint optimization framework results in a lower total transmit power than the two-stage approach.
2006
We consider a cognitive radio network in which a set of base stations make opportunistic unlicensed spectrum access to transmit data to their subscribers. As the spectrum of interest is licensed to another (primary) network, power and channel allocation must be carried out within the cognitive radio network so that no excessive interference is caused to any primary user. We are interested in spectrum-allocation/power-control schemes that maximize the spectrum utilization of the cognitive network while appropriately protecting primary users. While doing so, the control schemes must also meet the required signal to interference plus noise ratio (SINR) of each subscriber of the cognitive network. This problem can be formulated as a linear mixed (0-1) integer programming. Due to the high complexity in obtaining optimal spectrum-allocation/power-control schemes, we propose a suboptimal scheme that can be obtained at lower complexity while still achieving good spectrum utilization. This suboptimal scheme is constructed based on the idea of a dynamic interference graph that captures the interfering effects. Numerical studies of our control scheme are presented.
Primary User Enters the Game: Performance of Dynamic Spectrum Leasing in Cognitive Radio Networks
IEEE Transactions on Wireless Communications, 2000
Dynamic spectrum leasing (DSL) is one of the schemes proposed for dynamic spectrum sharing (DSS) in cognitive radio networks. In DSL, spectrum owners, denoted as primary users, dynamically adjust the amount of secondary interference they are willing to tolerate in response to the demand from secondary transmitters. In this correspondence we investigate how much can be gained by primary users if this limited interaction with secondary system is allowed, compared to a scheme in which the interference cap allowed by primary users is fixed a priori by a regulatory authority. To that end, we define performance metrics for both primary and secondary systems based on the theoretically achievable multiuser sum-rate of the secondary system and analyze both schemes' behavior with respect to different system parameters. This analysis shows that (i) in dynamic environments DSL based schemes may present an important advantage over other schemes with fixed interference constraints, and (ii) DSL schemes are robust against inaccurate a priori information that may degrade system performance.
Performance Analysis of Secondary Users in Cognitive Radio Networks With Dynamic Spectrum Allocation
IEEE Communications Letters, 2018
Cognitive radio technology improves the utilization of limited spectrum resources when wireless networks coexist. Using this technology, the spectrum holes in the frequency band of licensed users can be temporarily allocated to unlicensed users. This paper analyzes the opportunistic dynamic spectrum allocation method based on selecting the largest available spectrum hole to have the maximum possible transmission rate. This analysis proposes a theoretical model to find the probability distribution of the length of the largest available spectrum hole. The theoretical model works for any given number of total channels in the licensed frequency band. Numerical and simulation results confirm the accuracy of the proposed model.
2010 IEEE Global Telecommunications Conference GLOBECOM 2010, 2010
We study joint rate control and resource allocation with QoS provisioning that maximizes the total utility of secondary users in cognitive radio networks. We formulate and decouple the original utility optimization problem into separable subproblems and then develop an algorithm that converges to optimal rate control and resource allocation. The proposed algorithm can operate on different time-scale to reduce the amortized time complexity.