Efficient Spectrum Leasing via Randomized Silencing of Secondary Users

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.

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.

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.

We propose continuous power allocation strategies for secondary users (SUs) based on sensing the primary user (PU) channels in a multiband cognitive radio (CR) network. Unlike the conventional sensing-based spectrum sharing, where there are two transmit power levels corresponding to whether the PU is sensed present or not, in the proposed strategy, the power levels are continuous functions of the sensing statistics, and optimized with respect to the achievable rate of the SU. The continuous power allocation function is parameterized by some channel parameters of the PU and SU, and we treat the cases of perfect and quantized channel state information (CSI) separately, where the former provides an upper bound on the achievable rate with full channel information; and the latter constitutes an efficient practical power allocation method for the SU with statistic/partial channel information. The power control process consists of two phases: in the first phase, the SU listens to the multiple bands licensed to the PU and obtains the sensing statistics, e.g., the received signal energies on these bands; in the second phase, the SU adjusts its transmit power levels on these bands based on the sensing results. Optimal power allocation schemes are derived to maximize the achievable rate at the SU under several possible combinations of the peak/average transmit power constraints at the SU and the peak/average interference power constraints at the PU. Simulation results demonstrate that the proposed strategies can significantly improve the achievable throughput of the SU compared to the conventional methods.

A new information-theoretic model is proposed for underlay-based cognitive radio (CR), which imposes rate limitation on the secondary user (SU), whereas the traditional systems impose either interference or transmit power limitations. The channel is modeled as a twin-user interference channel constituted by the primary user (PU) and the SU. The achievable rate of the SU is derived based on the inner bound formulated by Han and Kobayashi, where the PU achieves the maximum attainable rate of the single-user point-to-point link. We show that it is necessary for the SU to allocate its full power for the “public” message that can be decoded both by the SU and by the PU. We also demonstrate that it is optimal for the PU to allocate its full power for the “private” message that can only be decoded by the PU if the level of interference imposed by the PU on the SU is “ergodically strong.” Similarly, it is optimal for the PU to allocate its full power for the public message that can be decoded both by the SU and PU if this interference is “ergodically weak.” These findings suggest that this power allocation is independent of the level of interference imposed by the SU on the PU. Furthermore, the achievable rate is analyzed as a function of the average level of interference. An interesting observation is that if the level of interference imposed by the SU on the PU is “ergodically weak,” the achievable rate becomes a monotonically increasing function of this interference, and it is independent of the level of interference imposed by the PU on the SU. Furthermore, we analyze the realistic imperfect channel estimation scenario and demonstrate that the channel estimation errors will not affect the optimal nature of the SU's power allocation.

In the underlay cognitive radio network, the secondary users are allowed to transmit concurrently with the primary users , which shows great potential to relieve the spectrum scarcity problem. However, it raises significant security issues at the physical layer due to the spectrum sharing approach. Different from most present research, in this paper we study the secure communication problem between secondary users where the primary receiver is a curious passive adversary, i.e., an eavesdropper. Specifically, we consider the worst but common case where the primary receiver can decode the messages from its primary transmitter successfully before trying to decode secondary user's confidential messages. To protect these messages from being eavesdropped, we employ a fullduplex secondary receiver who can broadcast jamming signals to degrade eavesdropper's channel quality while guaranteeing the quality of service (QoS) for primary transmission. Following this framework, we formulate a secrecy capacity maximization problem and obtain the optimal power allocation scheme to allocate power between the secondary transmitter and the fullduplex secondary receiver. Simulations are presented to show the superiority of the optimal scheme over baseline algorithms.

In this paper, we propose a cooperative spectrum sharing protocol for cognitive radio networks (CRNs) which operate in underlay mode with an automatic repeat-request (ARQ)-based primary user (PU) including primary transmitter (PT) and primary receiver (PR) and a bidirectionally communicating secondary user (SU) which consists of the nodes S1 and S2. In ARQ-based PU, ACKnowledgement/Negative-ACKnowledgement (ACK/NACK) messages are sent from PR to PT and listened by S1 and S2 to control the PU's packet success. Si (i=1 or 2) alerts both PT and PR if its reception from PT is successed or failed and PR considers the link from Si or PT, respectively. PU transmits its packet by accessing the spectrum alone or by cooperating with SU or under an interference caused by SU. If PT transmits alone its packet successfully, in the next time slot it transmits a new packet in underlay mode during which SU access the spectrum simultaneously with a tolerable interference level to improves the PU's performance. Conversely, if PT fails to transmit alone its packet and at least one of the nodes S1 and S2 success to decode it, then S1 or S2 cooperates with PT attending as a relay to enhance the PU's throughput in the next time slot during which PT stays silent. If both of S1 and S2 fail to decode PT's packet, PT retransmits its packet in underlay mode. When the first transmission of PT's packet is failed in underlay mode, PT retransmits this packet alone. We derive analytical expressions for the throughputs of PU and SU and show that the proposed protocol significantly improves the PU's throughput compared to non-CR scheme while stabilizing the SU's throughput at high SNR values.

In cognitive radio networks (CRNs), secure information transfer is of paramount importance for primary users (PUs), while secondary users (SUs) mainly desire to ease the starvation for transmission opportunities. To meet such different requirements, cooperation between PUs and SUs can be leveraged and therefore create a win-win situation. In this paper, we investigate cooperative spectrum access for CRNs, which targets to improve the secure transmission of PUs via cooperating SUs that would be incented by certain transmission opportunities. Two types of cooperation schemes are proposed, whereby the PU either cooperates with two individual SUs or a cluster of SUs, which are referred to as relay-jammer (R-J) scheme and cluster-beamforming (C-B) scheme, respectively. In R-J scheme, two individual SUs act as a relay and a friendly jammer to improve the PU's secrecy; In return, the PU allocates a fraction of access time for the SUs' transmission. To achieve the maximum secrecy rate, joint time and power allocation is considered. Particularly, the cooperating relay and jammer determine the optimal transmission power, while the PU decides the optimal time allocation strategy. In C-B scheme, the PU cooperates with a cluster of SUs to enhance the secrecy of the primary link via collaborative beamforming, where three different approaches are proposed for the scenarios with one eavesdropper, with multiple eavesdroppers, and without eavesdroppers' information, respectively. To maximize the secrecy rate, the weight selection and time allocation are also studied. Simulation results are given to validate the proposed schemes and demonstrate that the PU can significantly enhance the secrecy through cooperation.

Green communications is an inevitable trend for future communication network design, especially for a cognitive radio network. Power allocation strategies are of crucial importance for green cognitive radio networks. However, energy-efficient power allocation strategies in green cognitive radio networks have not been fully studied. Energy efficiency maximization problems are analyzed in delay-insensitive cognitive radio, delay-sensitive cognitive radio, and simultaneously delay-insensitive and delay-sensitive cognitive radio, where a secondary user coexists with a primary user and the channels are fading. Using fractional programming and convex optimization techniques, energy-efficient optimal power allocation strategies are proposed subject to constraints on the average interference power, along with the peak/average transmit power. It is shown that the secondary user can achieve energy efficiency gains under the average transmit power constraint, in contrast to the peak transmit power constraint. Simulation results show that the fading of the channel between the primary user transmitter and the secondary user receiver and the fading of the channel between the secondary user transmitter and the primary user receiver are favorable to the secondary user with respect to the energy efficiency maximization of the secondary user, whereas the fading of the channel between the secondary user transmitter and the secondary user receiver is unfavorable to the secondary user.

Cognitive radio methodologies have the potential to dramatically increase the throughput of wireless systems. Herein, control strategies which enable the superposition in time and frequency of primary and secondary user transmissions are explored in contrast to more traditional sensing approaches which only allow the secondary user to transmit when the primary user is idle. In this paper, the optimal transmission policy for the secondary user when the primary user adopts a retransmission-based error control scheme is investigated. The policy aims to maximize the secondary users' throughput, with a constraint on the throughput loss and failure probability of the primary user. Due to the constraint, the optimal policy is randomized, and determines how often the secondary user transmits according to the retransmission state of the packet being served by the primary user. The resulting optimal strategy of the secondary user is proven to have a unique structure. In particular, the optimal throughput is achieved by the secondary user by concentrating its transmission, and thus its interference to the primary user, in the first transmissions of a primary user packet. The rather simple framework considered in this paper highlights two fundamental aspects of cognitive networks that have not been covered so far: 1) the networking mechanisms implemented by the primary users (error control by means of retransmissions in the considered model) react to secondary users' activity; 2) if networking mechanisms are considered, then their state must be taken into account when optimizing secondary users' strategy, i.e., a strategy based on a binary active/idle perception of the primary users' state is suboptimal.

Energy-efficient power allocation for multi-user single-AF-relay underlay cognitive radio networks

In this chapter, we investigate one suboptimal power allocation scheme for an OFDM based cognitive radio system. Optical power allocation for secondary user in OFDM subcarrier is complex since it has a power as well as an interference constraint. Mathematical analysis shows that interference between primary and secondary in OFDM based system depends on theirs spectral distance. In our suboptimal method we consider the spectral distance between the secondary and primary user and modify the traditional water-filling algorithm. By applying our suboptimal power allocation method, it is possible that we can get good performance comparable to the optimal scheme. We compare our method with traditional power allocations schemes like equal power allocation and water filling power allocation. Result shows that distance dependent modified water filling (DDMWF) scheme can achieve the highest data rate for the cognitive radio based Secondary user.

The cooperation among the secondary users or among the secondary users and the primary users have proven to bring many benefits to both primary and secondary users in cognitive radio networks. In this paper, cooperative relaying in cognitive radio networks is studied for rateless coding error-control mechanism. For a pair of primary transmitter and receiver, we find the region in which any secondary or cognitive user can cooperate with the primary user in a constructive way. A queueing theoretical model is employed to describe the underlying system parameters and to create a mathematical framework for the analysis. The throughput performance of the secondary users is maximized based on the input traffic of the primary users. Using the unique properties of rateless codes, a low-complexity relay selection mechanism is also introduced. Through the experimental analysis, we show that the proposed rateless-coding-based cooperative mechanism can perform similar to the more complicated and more costly selective-repeat automatic repeat request algorithm. The numerical analysis using the Rapid Analysis of Queueing Systems (RAQS) software package is provided to support the findings.

Multi-input multioutput (MIMO) technique provides a promising solution to enhance the performance of wireless communication systems. In this paper, we consider antenna correlation at the transmitter in practical cognitive MIMO systems. What is more, a game-theoretic framework is conducted to analyze the optimum beamforming and power allocation such that each user maximizes its own rate selfishly under the transmitting power constraint and the primary user (PU) interference constraint. The design of the cognitive MIMO system is formulated as a noncooperative game, where the secondary users (SUs) compete with each other over the resources made available by the PUs. Interestingly, as the correlation parameter grows, the utility degrades. Nash equilibrium is considered as the solution of this game. Simulation results show that the proposed algorithm can converge quickly and clearly outperforms the strategy without game.

This paper adopts a multiobjective optimization (MOOP) approach to investigate the optimal link adaptation problem of orthogonal frequency division multiplexing (OFDM)-based cognitive radio (CR) systems, where secondary users (SUs) can opportunistically access the spectrum of primary users (PUs). For such a scenario, we solve the problem of jointly maximizing the CR system throughput and minimizing its transmit power, subject to constraints on both SU and PUs. The optimization problem imposes predefined interference thresholds for the PUs, guarantees the SU quality of service in terms of a maximum bit-error-rate (BER), and satisfies a transmit power budget and a maximum number of allocated bits per subcarrier. Unlike most of the work in the literature that considers perfect SU spectrum sensing capabilities, the problem formulation takes into account errors due to imperfect sensing of the PUs bands. Closed-form expressions are obtained for the optimal bit and power allocations per SU subcarrier. Simulation results illustrate the performance of the proposed algorithm and demonstrate the superiority of the MOOP approach when compared to single optimization approaches presented in the literature, without additional complexity. Furthermore, results show that the interference thresholds at the PUs receivers can be severely exceeded due to the perfect spectrum sensing assumption or due to partial channel information on links between the SU and the PUs receivers. Additionally, the results show that the performance of the proposed algorithm approaches that of an exhaustive search for the discrete optimal allocations with a significantly reduced computational effort.