Optimal power allocation for multiuser underlay cognitive radio networks under QoS and interference temperature constraints

This paper studies a cooperative cognitive radio network (CRN), where the primary system leases the licensed band to the secondary system for a fraction of time in exchange for the secondary user (SU) acting as a decode-and-forward relay. Our aim is to determine the cooperative resource allocation strategy among the primary user (PU) and SU so as to minimize both the total power consumption and the leased time. Considering the delay-sensitive applications in CRN, the proposed policy ensures delay-related quality-of-service (QoS) requirements of both PU and SU. To this end, a multi-objective optimization problem of power and time allocation is formulated based on the effective capacity. Via employing weighting method the optimization problem is transformed to a convex one and solved based on the lagrangian dual method. The proposed policy has been shown to be deterministic functions of delay QoS exponent and channel fading states. In particular, the power allocation is achieved by multi-level QoS based water-filling policy. Moreover, numerical results are provided to demonstrate the performance of the proposed resource allocation policy.

Power allocation for secondary users (SUs) in cognitive networks is an important issue to ensure the SUs’ quality of service. When the mutual interference between the primary users (PUs) and the SUs is taken into consideration, it is wanted to achieve the conflict-free power allocation while synchronously maximizing the capacity of the secondary network. In this paper, the optimal power allocation problem is considered in orthogonal frequency division multiplexing cognitive networks. The single SU case is primarily formulated as a constrained optimization problem. On this basis, the multiple SUs case is then studied and simulated in detail. During the analysis, the mutual interference among the PUs and the SUs is comprehensively formulated as the restrictions on the SU’s transmission power and the optimization problems are finally resolved by iterative water-filling algorithms. Consequently, the proposed power allocation scheme restrains the interference to the primary network, as well as maximizing the capacity of the secondary network. Specifying the multiple-SUs case, simulation results are exhibited in a simplified scenario to confirm the efficiency of the proposed water-filling algorithm, and the influence of the mutual interference on the power allocation and the system capacity is further illustrated.

Spectrum sharing and power allocation are interesting issues in cognitive radio networks. In our paper, we introduce a pricing scheme to demonstrate the spectrum sharing scenario between primary users and secondary users. We demonstrate the joint optimal allocation scheme of both spectrum and power for secondary users buying spectrum from multiple primary users. The joint optimal allocation scheme maximizes secondary users' utilities while primary users' utilities meet certain requirements. Moreover, we illustrate a distributed resource allocation scheme to jointly optimize usage of power and spectrum when each secondary user does not know others' buying strategies. Our simulation results show that under some utility requirements, the joint optimized resource allocation scheme has 3dB gain over that under even resource allocation.

This paper studies the case of an overlay cognitive radio network where the primary user leases spectral resources to the secondary user in exchange for cooperation, considering that both type of users have specific quality of service requirements. We investigate the problem of joint power and time allocation for the secondary access during the cooperative phase, with a view to optimizing the effective capacity of the primary user given an average energy constraint for the secondary user. Afterwards, the optimal power allocation of the secondary user for its own transmission phase is investigated in order to maximize the effective capacity of the secondary link. The proposed joint power and time allocation mechanism is compared with an optimal time/constant power allocation scheme and a less sophisticated baseline allocation scheme, i.e. power allocation under constant time and its superiority is proven for various network parameters. The reference model of one primary---one secondary user is extended to a general multi user cognitive radio network through the proposed pairing mechanism based on matching theory. Particularly, considering the remarks of the reference scenario, we propose two different matching schemes (with/without consideration of primary users' quality of service requirements) and we confirm their superiority compared to other matching mechanisms.

With the rapid development of wireless services and applications, the currently radio spectrum is becoming more crowded. How to accommodate more wireless services and applications within the limited radio spectrum becomes a big challenge faced by modern society. Cognitive radio (CR) is proposed as a promising technology to tackle this challenge by introducing secondary users (SUs) to opportunistically or concurrently access the spectrum allocated to primary users (PUs). Currently, there are two prevalent CR models: the spectrum sharing model and the opportunistic spectrum access model. In the spectrum sharing model, the SUs are allowed to coexist with the PUs as long as the interferences from SUs do not degrade the quality of service (QoS) of PUs to an unacceptable level. In the opportunistic spectrum access model, SUs are allowed to access the spectrum only if the PUs are detected to be inactive. These two models known as underlay and overlay schemes, respectively. This thesis studies a number of topics in CR networks under the framework of these two schemes. First, studied cognitive radio transmissions under QoS delay constraints. Initially, we focused on the concept: effective capacity for cognitive radio channels in order to identify the performance in the presence of QoS constraints. Both underlay and overlay schemes are studied taking into consideration the activity of primary users, and assuming the general case of channel fading as Gamma distribution. For this setting, we further proposed a selection criterion by which the cognitive radio network can choose the adequate mode of operation. Then, we studied the cognitive radio transmissions focusing on Rayleigh fading channel and assumed that no prior channel knowledge is available at the transmitter and the receiver. We investigated the performance of pilot-assisted transmission strategies. In particular, we analyzed the channel estimation using minimum mean-square-error (MMSE) estimation, and analyzed efficient resource allocation strategies. In both cases, power allocations and effective capacity optimization were obtained. Effective capacity and interference constraint were analyzed in both single-band and multi-band spectrum sensing settings. Finally, we studied optimal access probabilities for cognitive radio network using Markov model to achieve maximum throughput for both CR schemes.

In recent years, cognitive radio (CR) has received a great attention due to the ability to improve the spectrum utilization. It allows the secondary user (SU) in the CR network to opportunistically access the licensed spectrum of the primary user (PU). For this end, quality of service (QoS) requirements for both the PU and the SU should be guaranteed at the same time. These QoSs can be respectively translated into the interference temperature at the primary receiver and the received signal- to-interference-plus-noise-ratio (SINR) of the secondary receiver. In such a CR network, a power control can increase the energy efficiency by keeping the transmission power of the SU as low as possible within the QoS requirements. In this paper, we propose an autonomous distributed power control scheme for CR networks that considers the QoS requirements of the PU and the SU simultaneously. Since the transmission power of each SU is constrained so that the interference temperature at the primary receiver caused by all SUs does not exceed the interference tolerance of the PU, the QoS requirement for the PU is always guaranteed. Through the simulation results, we demonstrate that the proposed scheme never exceed the interference tolerance of the PU.

A cognitive radio (CR) network refers to a secondary network operating in a frequency band originally licensed/allocated to a primary network consisting of one or multiple primary users (PUs). A fundamental challenge for realizing such a system is to ensure the quality of service (QoS) of the PUs as well as to maximize the throughput or ensure the QoS, such as signal-to-interference-plus-noise ratios (SINRs), of the secondary users (SUs). In this paper, we study single-input multiple output multiple access channels (SIMO-MAC) for the CR network. Subject to interference constraints for the PUs as well as peak power constraints for the SUs, two optimization problems involving a joint beamforming and power allocation for the CR network are considered: the sum-rate maximization problem and the SINR balancing problem. For the sum-rate maximization problem, zero-forcing based decision feedback equalizers are used to decouple the SIMO-MAC, and a capped multi-level (CML) water-filling algorithm is proposed to maximize the achievable sum-rate of the SUs for the single PU case. When multiple PUs exist, a recursive decoupled power allocation algorithm is proposed to derive the optimal power allocation solution. For the SINR balancing problem, it is shown that, using linear minimum mean-square-error receivers, each of the interference constraints and peak power constraints can be completely decoupled, and thus the multi-constraint optimization problem can be solved through multiple single-constraint sub-problems. Theoretical analysis for the proposed algorithms is presented, together with numerical simulations which compare the performances of different power allocation schemes.

In cognitive radio networks, secondary users need to access the licensed spectrum while neither disturbing the transmissions of the primary users nor introducing much interference to other secondary users. Hence, proper power controlling is of paramount importance to ensure efficient system operation. The previous work on power control in cognitive networks mainly focuses on the interactions among a set of secondary users. The primary users' influence is rarely considered. In this paper, a new power control game model is formulated, by including the primary users into the player set of the game. The primary users are rewarded for sharing their licensed spectrum with secondary users by setting a reasonable interference cap for the secondary transmissions. However, we ensure a minimum required Quality of Service (QoS) for primary users by severely penalizing their utility if their required transmission quality is not met. Simultaneously, the secondary users achieve energy efficient transmissions while not introducing much interference to both the primary and other secondary users. We prove that the proposed cognitive power control game has a unique Nash equilibrium (NE). The numerical examples show that the proposed game theoretical power control algorithm can provide the secondary users with energy efficient transmissions and the primary users with reasonable monetary rewards, while not compromising their required QoS.

The most desired scheme in wireless communication (WC) technology is a cognitive radio network (CRN), which enhanced spectral efficiency. The main challenging problem for CRN is the power allocation (PA) scheme since it requires deliberating the quality of service (QoS) parameters for secondary users (SUs) through sustaining the power inference (PI) to Primary users (PUs) under the threshold of Interference Temperature (IT). The spectral insufficiency issues and interferences among the users possess a challenging task in CRN technology. To solve this issue, this paper statements shark smell optimisation (SSO) PA complications with optimal power constraints to diminishes the interference power and maximise capacity by permitting a large number of secondary users in CRN technology. In addition to that, multi-objective optimisation problems have been considered and targeted to maximise the minimum signal to noise ratio (SNR), network throughput utility and energy efficiency (EE). The proposed method is executed in MATLAB software, and the simulation results evaluate that the proposed strategy maintain ethical balance when compared to other existing approaches also it contributes to spectral scarcity issues resourcefully.

In this study, the problem of robust adaptive power control (PC) in an underlay cognitive radio network with multiple secondary users (SUs) and primary users (PUs) is considered. Due to the effects of uncertainties (i.e. estimation errors, delays), the optimal PC (resource allocation) cannot guarantee the quality of service of SUs and PUs under imperfect channel state information and interference power of PUs. A robust resource allocation problem is formulated to maximise sum throughput of SUs under individual power constraints and signal-to-interference-and-noise ratio constraints of SUs as well as interference temperature constraints of PUs, whereas channel uncertainties and interference uncertainties induced into the secondary system are modelled by multiplicative uncertainties. Under the worst-case approach, the problem is transformed into a geometric programming problem solved by Lagrange dual methods. The performance of the different algorithms and the impact of uncertainties are discussed according to several simulation results.

ABSTRACTThe pilot design is one of the key issues that has to be solved in order to improve the performance of non‐continuous orthogonal frequency division multiplexing (NC‐OFDM) systems in cognitive radio context. Equally‐spaced and equally‐powered pilot tones that are the optimal pilot design for conventional OFDM systems cannot be applicable to NC‐OFDM systems with the non‐continuous(NC) spectrum. In NC‐OFDM systems, the secondary users(SUs) communicate to each other by spectrum mapping the primary users(PUs)’ band to protect the PUs from interference. So the SUs’ available subcarriers’ positions and power allocation will be changed with PUs’ active state and interference constraints. The NC available spectrum and power distribution bring new challenges on system design, which make the pattern of pilots in the frequency domain vulnerable. Several recent researches have studied the optimal or suboptimal pilot designs under equally‐powered assumption. In this paper, we only focus on the comb‐type pilot design under uneven power distribution hypothesis for the NC‐OFDM transmission. Firstly, based on maximising each available subcarrier’ power under PUs’ interference temperature constraints, the pilot power constraints have been discussed, then the formula between pilot positions and pilot powers have been derived by minimising the channel estimation mean square error; moreover, a suboptimal pilot design under the pilot power constraints is also presented. The proposed pilot design cannot only obtain better channel estimation performance compared with previous pilot designs, but also consider the PUs’ communication reliability. Simulation results demonstrate the effectiveness of the proposed method. Copyright © 2013 John Wiley & Sons, Ltd.

In this paper, we introduce a new cooperative paradigm for secure communication in cognitive radio networks (CRNs) where secondary users (SUs) are allowed to access the spectrum of primary users (PUs) as long as they preserve the secure communication of PUs in the presence of malicious eavesdroppers. To do so, the SU transmission is divided into two hops: at first hop, the SU transmitter sends the information to a relay set and the SU receiver acts as a friendly jammer to disturb the overhearing of eavesdroppers and at the second hop, one of the relays is selected to pass the information to the SU receiver and the SU transmitter acts as a friendly jammer for the PU. In this new setup, the time duration for each hop, the power transmissions of all nodes in CRN, and relay selection at the second hop are allocated in such a way that the secrecy rate of the SU is maximized subject to the minimum required PU's secrecy rate. From primary service perspective, this transforms the possibly disturbing secondary service activities into a beneficial network element. We investigate instantaneous and ergodic resource allocation problems for perfect and imperfect channel state information (CSI). Since these problems are non-convex, we propose a solution based on decomposition of main optimization problem into three subproblems related to the power allocation, time allocation, and relay selection. We show that the power allocation problem can be transformed into a generalized geometric programming (GGP) model via the so-called scaled algorithm and it can be solved very efficiently. Simulation results indicate that in terms of the secondary secrecy rate, the proposed setup outperforms the conventional setup in which the secrecy rate of the PU is not guaranteed.

Spectrum is one of the most precious radio resources. With the increasing demand for wireless communication, efficiently using the spectrum resource has become an essential issue. With the Federal Communications Commission's (FCC) spectrum policy reform, secondary spectrum sharing has gained increasing interest. One of the policy reforms introduces the concept of an interference temperature - the total allowable interference in a spectral band. This means that secondary users can use different transmit powers as long as the sum of these power is less than the interference threshold. In this paper, we study two problems in secondary spectrum access with minimum signal to interference noise ratio (quality of service (QoS)) guarantee under an interference temperature constraint. First, when all the secondary links can be supported, a nonlinear optimization problem with the objective to maximize the total transmitting rate of the secondary users is formulated. The nonlinear optimization is solved efficiently using geometric programming techniques. The second problem we address is, when not all the secondary links can be supported with their QoS requirement, it is desirable to have the spectrum access opportunity proportional to the user priority if they belong to different priority classes. In this context, we formulate an operator problem which takes the priority issues into consideration. To solve this problem, first, we propose a centralized reduced complexity search algorithm to find the optimal solution. Then, in order to solve this problem distributively, we define a secondary spectrum sharing potential game. The Nash equilibria of this potential game are investigated. The efficiency of the Nash equilibria solutions are characterized. It is shown that distributed sequential play and an algorithm based on stochastic learning attain the equilibrium solutions. Finally, the performances are examined through simulations

Cognitive Radio Networks (CRN) are opportunistic networks which aim to harness the white space in the television frequency spectrum, on a need-to-need basis, without interfering the incumbent, called the Primary User (PU). Cognitive radios (CR) that sense the spectrum periodically for sensing the PU activity, are called Secondary Users (SU). CRNs are susceptible to two major attacks, Byzantine attacks and Primary User Emulation Attack (PUEA). Both the attacks are capable of rendering a CRN useless, by either interfering with the PU itself or capturing the entire channel for themselves. Byzantine attacks detection and mitigation is an important security issue in CRN. Hence, the current work proposes using a multi-Hidden Markov Model system with an aim to detect different types of random-Byzantine attacks. Simulation results show good detection rate across all the attacks.

In recent times, spectrum sensing and spectrum management become a crucial design issue in cognitive radio networks (CRN). To improve the spectrum utilization in CRN, the secondary users (SUs) will try to utilize the spectrum resource when it is unoccupied by the authorized primary users (PUs). At the same time, blockchain principle has been introduced to efficiently identify the legitimate SUs and allocate the spectrum resource as per the demand specified by the SUs. In this view, this article presents a new machine learning (ML) with blockchain‐based spectrum management technique in CRN. The proposed model undergoes three processes, namely spectrum sensing, blockchain‐based spectrum access, and malicious user (MU) identification. Initially, ML‐based extreme learning machine (ELM) technique is applied for spectrum sensing. Then, the presented blockchain approach provides secured spectrum allocation for SUs. Finally, the MUs are identified and to be blocked from accessing the available spectrum resource. An extensive simulation analysis is carried out to ensure the goodness of the proposed model. The obtained results indicated that the proposed model has offered better performance compared with other methods. The experimental outcome stated that under the presence of −20 dB SNR, the proposed method has attained a maximum detection rate of 0.68, whereas the KNN and OR rule methods have demonstrated a minimum detection rate of 0.58 and 0.5, respectively.