A wireless emergency communication network with a fixed allocation of spectrum resources cannot meet the tremendous demand for spectrum access when a crisis occurs. It is necessary to develop an effective spectrum access scheme to improve the performance of emergency communication systems. In this paper, we study a new emergency communication system combines cognitive radio technology and an emergency communication network. Emergency users can utility resources in a general network when traffic becomes congested in an emergency network. Non-reciprocal spectrum access scheme (NRA) and reciprocal spectrum access scheme (RA) for two heterogeneous cognitive networks, namely emergency network and general network are proposed to compare with traditional spectrum access scheme (TA). User behavior with each scheme is modeled by continuous-time Markov chains. Moreover, the blocking and dropping probabilities of users in two heterogeneous cognitive networks are derived as the performance metrics. In addition, the throughput and the spectrum utilization rate of the system are evaluated. Finally, we compare the performance of three dynamic spectrum access schemes. The simulation results show that the RA scheme is an effective scheme to enhance the performance of emergency systems.

This paper proposes a reduced-complexity multiband multiple-input multiple-output (MIMO) receiver that can be used in cognitive radios. The proposed receiver uses heterodyne reception implemented with a wide-passband band-pass filter in the radio frequency (RF) stage. When an RF Hilbert transformer is utilized in the receiver, image-band interference occurs because of the transformer's imperfections. Thus, the imperfection of the Hilbert transformer is corrected in the intermediate frequency (IF) stage to reduce the hardware complexity. First, the proposed receiver estimates the channel impulse response in the presence of the strong image-band interference signals. Next, the coefficients are calculated for the correction of the imperfection at the IF stage, and are fed back to the IF stage through a feedback loop. However, the imperfection caused by the digital-to-analog (D/A) converter and the baseband amplifier in the feedback loop corrupts the coefficients on the way back to the IF stage. Therefore, the proposed receiver corrects the imperfection of the analog devices in the feedback loop. The performance of the proposed receiver is verified by using computer simulations. The proposed receiver can maintain its performance even in the presence of strong image-band interference signals and imperfection of the analog devices in the feedback loop. In addition, this paper also reveals the condition for rapid convergence.

In this article, we propose a method to reduce the impact of primary traffic on spectrum sensing performance. In practice, the sensing performance is degraded by noise-only sample in the spectrum sensing time. Therefore, we employ a time of primary user (PU) signal arrival detector in order to remove the noise-only portion. Then, we employ equal-weight-based energy detection (EWED) to provide the detection decision. The analysis and simulation results show that there exists an optimal early time of arrival (ToA) false alarm which provides better performance compared to the use of a single EWED scheme.

An improved spectrum sensing method based on PN autocorrelation (PNAC) for Digital Terrestrial Television Multimedia Broadcasting (DTMB) system is proposed in this paper. The low bound of miss-detection probability and the decision threshold for a given false alarm probability are studied. The performances of proposed method and existing methods are compared through computer simulations under both non-time dispersive channel and time dispersive channel. Simulation results show that the proposed method has better performance than the original PNAC-based method, and is more robust to both carrier frequency offset (CFO) and time dispersion of the channel than the existing method based on PN cross-correlation (PNCC).

It is well known that cognitive radio (CR) techniques have great potential for supporting future demands on the scarce radio spectrum resources. For example, by enabling the utilization of spectrum bands temporarily not utilized by primary users (PUs) licensed to operate on those bands. Spectrum sensing is a well-known CR technique for detecting those unutilized bands. However, the spectrum sensing outcomes cannot be perfect and there will always be some misdetections and false alarms which will affect the performance thereby degrading the quality of service (QoS) of PUs. Continuous time Markov chain (CTMC) based modeling has been widely used in the literature to evaluate the performance of CR networks (CRNs). A major limitation of the available literature is that all the key factors and realistic elements such as the effect of imperfect sensing and state dependent transition rates are not modeled in a single work. In this paper, we present a CTMC based model for analyzing the performance of CRNs. The proposed model differs from the existing models by accurately incorporating key elements such as full state dependent transition rates, multi-channel support, handoff capability, and imperfect sensing. We derive formulas for primary termination probability, secondary success probability, secondary blocking probability, secondary forced termination probability, and radio resource utilization. The results show that incorporating fully state dependent transition rates in the CTMC can significantly improve analysis accuracy, thus achieving more realistic and accurate analytical model. The results from extensive Monte Carlo simulations confirm the validity of our proposed model.

Cognitive beamforming exploiting spatial opportunity is an attractive technique for secondary users to coexist with primary users in cognitive radio environments. If perfect channel state information of the interfering link is available, interference from a secondary transmitter to a primary receiver can be perfectly pre-nulled by choosing the ideal transmit beam. In practice, however, there is channel estimation error due to noise and the time-varying channels. To minimize the residual interference due to those channel estimation errors, channel prediction based on auto regressive (AR) model is introduced in this paper. Further, to cope with extremely rapidly-varying channels, a cognitive transmit power control technique is proposed as well. By combining channel prediction and transmit power control in cognitive beamforming, the cognitive users can share the spectrum with the primary users with a limited interference level in time-varying channels.

The heterogeneous network (HetNet), which deploys small cells such as picocells, femotcells, and relay nodes within macrocell, is regarded as a cost-efficient and energy-efficient approach to resolve increasing demand for data bandwidth and thus has received a lot of attention from research and industry. Since small cells share the same licensed spectrum with macrocells, concurrent transmission induces severe interference, which causes performance degradation, particularly when coordination among small cell base stations (BSs) is infeasible. Given the dense, massive, and unplanned deployment of small cells, mitigating interference in a distributed manner is a challenge and has been explored in recent papers. An efficient and innovative approach is to apply cognitive radio (CR) into HetNet, which enables small cells to sense and to adapt to their surrounding environments. Consequently, stations in each small cell are able to acquire additional information from surrounding environments and opportunistically operate in the spectrum hole, constrained by minimal inducing interference. This paper summarizes and highlights the CR-based interference mitigation approaches in orthogonal frequency division multiple access (OFDMA)-based HetNet networks. With special discussing the role of sensed information at small cells for the interference mitigation, this paper presents the potential cross-layer facilitation of the CR-enable HetNet.

Dynamic spectrum leasing (DSL) is regarded as a promising dynamic spectrum sharing (DSS) scheme both to improve the spectrum revenue of primary users (PUs) and to guarantee the QoS of secondary users (SUs). A pricing-based DSL termed PBDSL is formulated as a Stackelberg DSL game model, where PUs as players entering the interacting game with multiple SUs. The strategic design contains both optimal spectrum pricing schemes (including unit spectrum/interference price and interference sensitivity distributed adjustments) of PUs for the specific shared/leased spectrum and optimal transmission strategies (e.g., transmit power and bandwidth) of SUs. To capture two types of competition relationships among multiple SUs and between SUs and PUs, we investigate two intra-game models of multiple PUs and SUs, respectively, which interact with each other to constitute the final Stackelberg DSL game. The existence and uniqueness of Stackelberg equilibrium solution (SES) are analyzed and proved for presented games, based on which a joint multi-stage PBDSL algorithm is presented to approximate the optimal equilibrium strategies. Numerical results demonstrate the convergence property of the interactive decision-making process, and verify the effectiveness of the proposed algorithm, in a comparison with the Nash equilibrium solution (NES)-based approach.

For opportunistic spectrum access (OSA), spectrum management is a key function to effectively utilize white space without causing harmful interference to incumbent receivers. Geo-location database approaches using radio propagation estimation have been regarded as practical spectrum management methods. However, propagation models inevitably fail to accurately estimate the path loss in actual radio environments, resulting in estimation error of carrier to interference ratio (CIR) of the incumbent receivers. This could prevent white space from being efficiently utilized, because the allowable transmit power of the opportunistic system has to be limited to keep the CIR at the required level. To improve the accuracy of CIR estimation, we propose the new concept of Interference Monitoring which works in combination with spectrum management. In this method, a monitoring node located near the incumbent receivers actually measures both the interference signals and the incumbent signals. Using the measurement results, the CIR estimates are corrected based on the minimum mean square error (MMSE) criterion. The proposed Interference Monitoring can be extended to establish cooperation among multiple monitoring nodes and thus spatial diversity. Analytical evaluations assuming a simple cellular system model show that Interference Monitoring can more accurately estimate CIR, and thus it can significantly increase the allowable transmit power. For an urban macro cell, Interference Monitoring with a single node achieved about a 6.5 dB increase in the transmit power; Cooperative Interference Monitoring with 4 nodes achieved about a 13.5 dB increase. Thus, Interference Monitoring-based spectrum management can maximize opportunities for white space utilization without imposing additional interference to the incumbent system.

Spectrum sharing cognitive radio (CR) with maximal ratio combining (MRC) diversity under asymmetric fading is studied. Specifically, the channel on the secondary transmitter (STx) to the secondary receiver (SRx) link is Nakagami-m distributed while the channel on the STx to the primary receiver (PRx) link is Rayleigh distributed, and the channel state information (CSI) on the STx-PRx link is assumed to be outdated due to feedback delay. The outage capacity of the secondary user (SU) is derived under the average interference and peak transmit power constraints. The results supported by simulations are presented and show the effects of various system parameters on the outage capacity. Particularly, it is shown that the outdated CSI has no impact on the outage capacities in the cases of low peak transmit power constraint and zero-outage probability. It is also shown that MRC diversity can significantly improve the outage capacity especially for the zero-outage capacity and the outage capacity under low outage probability.

Among the cognitive radio technologies, cooperative spectrum sensing has been corroborated to be an effective approach to counter channel fading. Recent research about it is mainly with the assumption that secondary users (SUs) are synchronous with primary users (PUs). In this letter, we discuss the asynchronous situation for the first time, which means SUs have no idea about the communication time table of PUs' network. Based on the ON/OFF channel model, we derive the detection and false alarm probabilities, and the optimal sensing parameters under such asynchronous scenario. Simulation results are shown in the end.

In OFDM-based cognitive radio systems, due to the out-of-band leakage from the secondary transmission, the interference to primary users must be considered in order to guarantee the quality of service of the primary transmission. For multiuser cognitive radio systems, there exist two crucial issues in resource allocation: fairness and efficiency, in order to balance the two issues, we proposed a new utility-based cross-layer resource allocation algorithm, which can not only control the interference to primary users caused by secondary users, but also balance the spectral efficiency and fairness among cognitive users. Further, the optimal NP-hard resource allocation problem in multiuser OFDM-based systems is reduced to the sub-optimal solution by dividing the original problem into the subcarrier allocation problem and the power allocation problem. It is shown that the proposed algorithm can obtain the best performance in terms of the average rate or the utility among existing algorithms, and at the same time, all the users obtain fair resource allocation.

In spectrum sharing cognitive radio (CR) networks, secondary user (SU) is allowed to share the same spectrum band concurrently with primary user (PU), with the condition that the SU causes no harmful interference to the PU. In this letter, the ergodic and outage capacity loss constraints are proposed to protect the PU according to its service types. We investigate the performance of the SU in terms of ergodic capacity under various power allocation policies of the PU. Specifically, three PU power allocation policies are considered, namely waterfilling, truncated channel inversion with fixed rate (TIFR) and constant power allocation. We obtain the ergodic capacities of the SU under the three PU power allocation policies. The numerical results show that the PU waterfilling and TIFR power allocation policies are superior to the PU constant power allocation in terms of the capacity of the PU. In particular, it is shown that, with respect to the ergodic capacity of the SU, the PU waterfilling power allocation is superior to the PU constant power allocation, while the PU TIFR power allocation is inferior to the PU constant power allocation.

In this letter, we analyze the outage performance of cognitive spectrum sharing in two-way relaying systems. We derive expressions of outage probability for the primary and secondary network over independent but not necessarily identically distributed (i.n.i.d.) Rayleigh fading channels. Monte Carlo simulations are presented to verify the theoretical analyses.

In this work, we analyze the performance of cognitive amplify-and-forward (AF) relay networks under the spectrum sharing approach. In particular, by assuming that the AF relay operates in the semi-blind mode (fixed-gain), we derive the exact closed-form expressions of the outage probability for the cognitive relaying (no direct link) and cognitive cooperative (with direct link) systems. Simulation results are presented to verify the theoretical analysis.

This paper proposes a novel scheme called as“frequency domain imbalance estimation” that estimates the imbalance of the Hilbert transformer in heterodyne multimode/band receivers with baseband automatic gain control (AGC). The proposed scheme uses correlation matrices in the frequency domain. This enables the receivers to keep high transmission performance in spite of the imbalance of the analog Hilbert transformer, by offsetting the imbalance. Moreover, the baseband AGC relaxes the requirement of the baseband A/D converter. The performance of imbalance estimation and imbalance cancellation is verified by computer simulation. As a result, it is shown that the proposed scheme not only estimates the imbalance of Hilbert transformer with extremely high precision, but also cancels the image-band interference such that it achieves the theoretical performance.

Based on a proposed frame structure with an unequal sensing slot duration for each channel, and two sensing scenarios (with or without cooperation), a joint channel and sensing time assignment is suggested to maximize the uplink throughput of the centralized multi-band cognitive radio network with the consideration of the mutual interference among the secondary users (SUs). Firstly, the channel assignment is performed by using the proposed Delta Non-square Hungarian (DNH), which is a modified iterative Hungarian algorithm distinguished by throughput increment maximization and non-square weight matrix. Simulation results illustrate that DNH has significant advantages in enhancing the throughput and reducing the computational complexity. Moreover, a hybrid channel assignment, also performed by DNH, is improved based on the two sensing scenarios to maximize the throughput while efficiently limiting the interference power to primary users. Secondly, the convexity of the throughput functions within the range of sensing time is proved under the proposed frame structure, and then the maximum throughput is achieved through the steepest descent method-based sensing time assignment. Both of these results are corroborated by simulations.

Recently, cooperative spectrum sensing is being studied to greatly improve the sensing performance of cognitive radio networks. To develop an adaptable cooperative sensing algorithm, an important issue is how to properly induce selfish users to participate in spectrum sensing work. In this paper, a new cognitive radio spectrum sharing scheme is developed by employing the trust-based bargaining model. The proposed scheme dynamically adjusts bargaining powers and adaptively shares the available spectrum in real-time online manner. Under widely different and diversified network situations, this approach is so dynamic and flexible that it can adaptively respond to current network conditions. Simulation results demonstrate that the proposed scheme can obtain better network performance and bandwidth efficiency than existing schemes.

In this study, we propose a cooperative sensing with distributed pre-detection for gathering sensing information on shared primary system. We have proposed a system that gathers multiple sensing information by using the orthogonal narrowband signal; the system is called the orthogonal frequency-based sensing information gathering (OF-SIG) method. By using this method, sensing information from multiple secondary nodes can be gathered from the surrounding secondary nodes simultaneously by using the orthogonal narrowband signals. The advantage of this method is that the interference from each node is small because a narrowband tone signal is transmitted from each node. Therefore, if appropriate power and transmission control are applied at the surrounding nodes, the sensing information can be gathered in the same spectrum as the primary system. To avoid interference with the primary receiver, we propose a cooperative sensing with distributed pre-detection for gathering sensing information in each node by limiting sensing node power. In the proposed method, the number of sensing information transmitting nodes depends on the pre-detection ability of the individual sensing at each node. Then the secondary node can increase the transmit power by improving the sensing detection ability, and the secondary node can gather the sensing information from the surrounding secondary nodes which are located more far by redesign the transmit power of the secondary nodes. Here, we design the secondary transmit power based on OF-SIG while considering the aggregated interference from multiple sensing nodes and individual sensing ability. Finally we confirm the performance of the cooperative sensing of the proposed method through computer simulation.

In this paper, low-complexity generalized singular value decomposition (GSVD) based beamforming schemes are proposed for a cognitive radio (CR) network in which multiple secondary users (SUs) with multiple antennas coexist with multiple primary users (PUs). In general, optimal beamforming, which suppresses the interference caused at PUs to below a certain threshold and maximizes the signal-to-interference-plus-noise ratios (SINRs) of multiple SUs simultaneously, requires a complicated iterative optimization process. To overcome the computational complexity, we introduce a signal-to-leakage-plus-noise ratio (SLNR) maximizing beamforming scheme in which the weight can be obtained by using the GSVD algorithm, and does not require any iterations or matrix squaring operations. Here, to satisfy the leakage constraints at PUs, two linear methods, zero forcing (ZF) preprocessing and power allocation, are proposed.