We propose optimal power allocation schemes for a secondary cognitive user sharing spectrum with a primary user under different interference power constraints in Rayleigh fading channels. Specifically, we consider a practical scenario in which the secondary user has a fixed transmission rate and the instantaneous channel state of the interference channel is not available to the secondary user. Simulation results verify the feasibility of the proposed schemes and evaluate the effective transmission rate loss due to the incomplete channel state information.

This letter proposes a novel decision fusion algorithm for cooperative spectrum sensing in cognitive radio sensor networks where a reinforcement learning algorithm is utilized at the fusion center to estimate the sensing performance of local spectrum sensing nodes. The estimates are then used to determine the weights of local decisions for the final decision making process that is based on the Chair-Vashney optimal decision fusion rule. Simulation results show that the sensing accuracy of the proposed scheme is comparable to that of the Chair-Vashney optimal decision fusion based scheme even though it does not require any knowledge of prior probabilities and local sensing performance of spectrum sensing nodes.

The sensing scheme based on the generalized likelihood ratio test (GLRT) technique has attracted a lot of research interest in the field of cognitive radios (CR). Although its potential advantages in detecting correlated primary signal have been illustrated in prior work, no theoretical analysis of the positive effects of the correlation has appeared in the literature. In this letter, we derive the theoretical false-alarm and detection probabilities of GLRT detector. The theoretical analysis shows that, in the low signal-to-noise ratio (SNR) region, the detector's performance can be improved by exploiting the high correlations between the primary signal samples. The conclusions of the analysis are verified by numerical simulation results.

Wireless regional area network (WRAN) is intended to offer the fixed wireless access services using cognitive radio technology in the TV white space. Therefore, WRAN shall minimize the transmission power so that harmful interference is not imposed on the licensed users operating in the TV bands. In this paper, we propose a processing block that offers improvements in the SNR and diversity gain using the block to algebraically process two constellation symbols. Thus, the transmission power can be reduced by an amount equal to the gains. The simulation result shows that the proposed scheme has a better bit error performance than the transmission scheme defined in the IEEE 802.22 draft standard.

It is known that a heterodyne multimode receiver implemented with a single RF (Radio Frequency) receiver suffers from image-band interference due to imbalance, i.e. the phase error and the gain imbalance of the RF Hilbert transformer. The blind image band interference canceler with deterministic imbalance estimation that has been proposed mitigates the image-band interference. This performance of the image-band interference canceler is analyzed theoretically in this paper. As a result, it is revealed that estimation accuracy of the deterministic imbalance estimation is improved slightly as the imbalance becomes greater. In addition, it is also shown that the deterministic estimation achieves better performance as the power of image-band interference increases. The performance is confirmed by computer simulation.

The performance of spectrum sensing in cognitive radio can be improved by employing multiple antennas. In this letter, the effect of antenna correlation on the performance improvement by deploying multiple antennas in the sensing node of the secondary system is investigated. It is proved mathematically that in the regime of low SNR, with antenna correlation, the secondary sensing node can achieve almost the same performance improvement as that without correlation. Simulation results verify the conclusions.

Mobile operators need to migrate from 2G to 3G networks in a cost-effective manner. Cognitive radio systems are currently being investigated as a promising solution to achieve spectrum efficiency by allowing coexistence of unlicensed (secondary) networks and licensed (primary) networks. However, conventional mechanisms to operate these systems incur additional complexity and fail to maximize network performance. In this paper, we propose a pilot sensing and frequency selection method with low complexity for OFDMA-based cognitive radio systems. Subject to the interference constraints imposed by the primary network, capacity maximization problems involving both up-link and down-link connections are considered for overall network performance improvement. The throughput and outage probability of the proposed method are evaluated by simulations. Our proposed method shows outstanding performance if the channel varies frequently in the primary network and the frequency reuse factor of the primary network is high.

The traditional spectrum auctions require a central auctioneer. Then, the secondary users (SUs) can bid for spectrum in multiple auction or sealed auction way. In this paper, we address the problem of distributed spectrum sharing in the cognitive networks where multiple owners sell their spare bands to multiple SUs. Each SU equips multi-interface/multi-radio, so that SU can buy spare bands from multiple owners. On the other hand, each owner can sell its spare bands to serval SUs. There are two questions to be addressed for such an environment: the first one is how to select bands/the owners for each SU; the second one is how to decide the competitive prices for the multiple owners and multiple SUs. To this end, we propose a two-side multi-band market game theoretic framework to jointly consider the benefits of all SUs and owners. The equilibrium concept in such games is named core. The outcomes in the core of the game cannot be improved upon by any subset of players. These outcomes correspond exactly to the price-lists that competitively balance the benefits of all SUs and owners. We show that the core in our model is always non-empty. When the measurement of price takes discrete value, the core of the game is defined as discrete core. The Dynamic Multi-band Sharing algorithm (DMS) is proposed to converge to the discrete core of the game. With small enough measurement unit of price, the algorithm can achieve the optimal performance compared with centralized one in terms of the system utility.

We consider the problem of transmit power and bit rate allocation for OFDM based cognitive radio systems. An efficient allocation algorithm which mainly consists of two steps is proposed to maximize the sum rate of secondary users. In the first step of the algorithm, original nonlinear problem is converted to a convex problem which is solved by dual methods, and in the second step the final resource allocation results is obtained via iterative power rescale operation. Numerical results show the effectiveness of the proposed algorithm.

We present an orthogonal frequency division multiple access (OFDMA) based multichannel slotted ALOHA for cognitive radio networks (OMSA-CR). The performance of an infinite population based OMSA-CR system is analyzed in terms of channel capacity, throughput, delay, and packet capture effect. We investigate the channel capacity for OMSA-CR with perfect or imperfect spectrum sensing. We introduce the proposed CR MAC based on two channel selection schemes: non-agile channel selection (NCS) and agile channel selection (ACS). Comparing them, we show the tradeoff between complexity and system performance. We verify the proposed CR system model using numerical analysis. In particular, using simulation with a finite populated linear feedback model, we observe the OMSA-CR MAC tradeoff between throughput and minimum delay whose results matched those of the analytical framework. Numerical results for the proposed system throughput are also compared to conventional MACs, including pure ALOHA based CR MAC.

A cognitive radio will have to sense and discover the spectral environments where it would not cause primary radios to interfere. Because the primary radios have the right to use the frequency, the cognitive radios as the secondary radios must detect radio signals before use. However, the secondary radios also need identifying the primary and other secondary radios where the primary radios are vulnerable to interference. In this paper, a method of simultaneously identifying signals of primary and secondary radios is proposed. The proposed bandwidth differentiation assumes the primary and secondary radios use orthogonal frequency division multiplexing (OFDM), and the secondary radios use at the lower number of subcarriers than the primary radios. The false alarm and detection probabilities are analytically evaluated using the characteristic function method. Numerical evaluations are also conducted on the assumption the primary radio is digital terrestrial television broadcasting. Result showed the proposed method could achieve the false alarm probability of 0.1 and the detection probability of 0.9 where the primary and secondary radio powers were 2.5 dB and 3.6 dB higher than the noise power. In the evaluation, the reception signals were averaged over the successive 32 snapshots, and the both the primary and secondary radios used QPSK. The power ratios were 4.7 dB and 8.4 dB where both the primary and secondary radios used 64QAM.

This paper addresses the coexistence issue of distributed heterogeneous networks where the network nodes are cognitive radio terminals. These nodes, operating as secondary users (SUs), might interfere with primary users (PUs) who are licensed to use a given frequency band. Further, due to the lack of coordination and the dissimilarity of the radio access technologies (RATs) among these wireless nodes, they might interfere with each other. To solve this coexistence problem, we propose an architecture that enables coordination among the distributed nodes. The architecture provides coexistence solutions and sends reconfiguration commands to SU networks. As an example, time sharing is considered as a solution. Further, the time slot allocation ratios and transmit powers are parameters encapsulated in the reconfiguration commands. The performance of the proposed scheme is evaluated in terms of the coexistence between PUs and SUs, as well as the coexistence among SUs. The former addresses the interference from SUs to PUs, whereas the latter addresses the sharing of an identified spectrum opportunity among heterogeneous SU networks for achieving an efficient spectrum usage. In this study, we first introduce a new parameter named as quality of coexistence (QoC), which is defined as the ratio between the quality of SU transmissions and the negative interference to PUs. In this study we assume that the SUs have multiple antennas and employ fixed transmit power control (fixed-TPC). By using the approximation to the distribution of a weighted sum of chi-square random variables (RVs), we develop an analytical model for the time slot allocation among SU networks. Using this analytical model, we obtain the optimal time slot allocation ratios as well as transmit powers of the SU networks by maximizing the QoC. This leads to an efficient spectrum usage among SUs and a minimized negative influence to the PUs. Results show that in a particular scenario the QoC can be increased by 30%.

To satisfy the requirement of a unified platform which can flexibly deal with various wireless radio systems, we proposed and implemented a heterogeneous network system composed of distributed flexible access points and a protocol-free signal processing unit. Distributed flexible access points are remote RF devices which perform the reception of multiple types of radio wave data and transfer the received data to the protocol-free signal processing unit through wired access network. The protocol-free signal processing unit performs multiple types of signal analysis by software. To realize a highly flexible and efficient radio wave data reception and transfer, we employ the recently developed compressed sensing technology. Moreover, we propose a combined Nyquist and compressed sampling method for the decoding signals to be sampled at the Nyquist rate and for the sensing signals to be sampled at the compressed rate. For this purpose, the decoding signals and the sensing signals are converted into the intermediate band frequency (IF) and mixed. In the IF band, the decoding signals are set at lower center frequencies than those of the sensing signals. The down converted signals are sampled at the rate of four times of the whole bandwidth of the decoding signals plus two times of the whole bandwidth of the sensing signals. The purpose of above setting is to simultaneously conduct Nyquist rate and compressed rate sampling in a single ADC. Then, all of odd (or even) samples are preserved and some of even (or odd) samples are randomly discarded. This method reduces the data transfer burden in dealing with the sensing signals while guaranteeing the realization of Nyquist-rate decoding performance. Simulation and experiment results validate the efficiency of the proposed method.

This letter proposes a novel censor-based scheme for cooperative spectrum sensing on Cognitive Radio Sensor Networks. A Takagi-Sugeno's fuzzy system is proposed to make the decision on the presence of the licensed user's signal based on the observed energy at each cognitive sensor node. The local spectrum sensing results are aggregated to make the final sensing decision at the fusion center after being censored to reduce transmission energy and reporting time. Simulation results show that significant improvement of the spectrum sensing accuracy, and saving energy as well as reporting time are achieved by our scheme.

The spectrum handoff problem for cognitive radio systems is considered in this paper. The secondary users (SUs) can only opportunistically access the spectrum holes, i.e. the frequency channels unoccupied by the primary users (PUs). As long as a PU appears, SUs have to vacate the channel to avoid interference to PUs and switch to another available channel. In this paper, a prediction-based spectrum handoff scheme is proposed to reduce the negative effect (both the interference to PUs and the service block of SUs) during the switching time. In the proposed scheme, a hidden Markov model is used to predict the occupancy of a frequency channel. By estimating the state of the model in the next time instant, we can predict whether the frequency channel will be occupied by PUs or not. As a cross-layer design, the spectrum sensing performance parameters false alarm probability and missing detection probability are taken into account to enhance accuracy of the channel occupancy prediction. The proposed scheme will react on the spectrum sensing algorithm parameters while the spectrum handoff performance is significantly affected by them. The interference to the PUs could be reduced obviously by adapting the proposed spectrum handoff scheme, associated with a potential increase of switch delay of SUs. It will also be helpful for SUs to save broadband scan time and prefer an appropriate objective channel so as to avoid service block. Numerical results demonstrate the above performance improvement by using this prediction-based scheme.

From the viewpoint of service availability, which is an important evaluation factor in communication quality, we analytically study the performance improvement of heterogeneous radio networks that cooperatively select one system from among multiple communication systems. It is supposed herein that the heterogeneous network selects one system with the larger throughput or with the smaller time delay. To this end, we firstly derive analytical methods using the probability density function of the performance characteristics of the communication systems consisting of the heterogeneous radio network. The analytical method described here is comparatively general and enables the handling of cases where complete cooperation can and cannot be achieved in the heterogeneous network. As for the performance characteristics, we conduct an experiment using the wireless LAN to establish the probability distribution models of the throughput and time delay in the communication system. Using the analytical method and the experimental model obtained, we calculate the performance improvement by cooperative operation in the heterogeneous network. The equational expression to obtain the theoretical performance improvement limit is also investigated through the analytical equations.

A channel-hopping medium access control (MAC) protocol is proposed for cognitive operation of the 802.16d Mesh networks. The proposal mainly includes a channel-hopping algorithm of channel accessing for control messages transmission and reception, an algorithm of bandwidth allocation in cognitive operation, a cognition-enhanced frame structure, a method of spectrum sensing results reporting, and a method of incumbent detection. Compared to other studies, the channel-hopping algorithm for control messages transmission and reception requires no extra common control channels and operation of mesh clusters, thus it is more cost-effective and simpler in operation. Analysis shows that with this algorithm a Mesh node with any available channels has fair opportunities to receive beacon and network configuration information. Numerical results show that, compared to the mesh cluster method, the proposed channel-hopping algorithm has gain, e.g., as high as 3 times, in getting the data scheduling control messages received by one-hop neighbors, thus it has advantages in minimizing bandwidth allocation collisions. The algorithm of bandwidth allocation details the three-way handshake framework for bandwidth application and grant that is defined in 802.16d Mesh standard, and it enables dynamical resource allocations in cognitive operations. The feasibility of the channel-hopping MAC protocol is confirmed by simulations. And simulation results show that with the parameters set, a normalized aggregate saturation throughput of about 70% is achievable.

In a periodic spectrum sensing framework where each frame consists of a sensing block and a data transmitting block, increasing sensing duration decreases the probabilities of both missed opportunity and interference with primary users, but increasing sensing duration also decreases the energy efficiency and the transmitting efficiency of the cognitive network. Therefore, the sensing duration to use is a trade-off between sensing performance and system efficiencies. The relationships between sensing duration and state transition probability are analyzed firstly, when the licensed channel stays in the idle and busy states respectively. Then a state transition probability based sensing duration optimization algorithm is proposed, which can dynamically optimize the sensing duration of each frame in the current idle/busy state by predicting each frame's state transition probability at the beginning of the current state. Analysis and simulation results reveal that the time-varying optimal sensing duration increases as the state transition probability increases and compared to the existing method, the proposed algorithm can use as little sensing duration in each frame as possible to satisfy the sensing performance constraints so as to maximize the energy and transmitting efficiencies of the cognitive networks.

Selections of radio access networks by terminals are currently not coordinated and utilizations of the radio resources are not balanced. As a result, radio resources on some radio systems are occupied even though others can afford. In this paper, in order to provide a framework to resolve this issue, Cognitive Wireless Router (CWR) system is proposed for distributed management and independent reconfiguration of heterogeneous wireless networks. The proposed system selects appropriate operational frequency bands and radio systems to connect to the Internet in corporation between the CWRs and a server and therefore can provide optimized wireless Internet access easily even in environments without wired networks. The developed prototype system reconfigures the radio devices to connect to the Internet in 27 seconds at most. It is revealed that this reconfiguration time can be shortened to less than 100 ms by elaborating its procedure. It is also clarified that network data speed required at the server to deal with 10,000 CWRs is only 4.1 Mbps.

A Gaussian MIMO broadcast channel (GMBC) models the MIMO transmission of Gaussian signals from a transmitter to one or more receivers. Its capacity region and different precoding schemes for it have been well investigated, especially for the case wherein there are only transmit power constraints. In this paper, a special case of GMBC is investigated, wherein receive power constraints are also included. By imposing receive power constraints, the model, called protected GMBC (PGMBC), can be applied to certain scenarios in spatial spectrum sharing, secretive communications, mesh networks and base station cooperation. The sum capacity, capacity region, and application examples for the PGMBC are discussed in this paper. Sub-optimum precoding algorithms are also proposed for the PGMBC, where standard user precoding techniques are performed over a BC with a modified channel, which we refer to as the "protection-implied BC." In the protection-implied BC, the receiver protection constraints have been implied in the channel, which means that by satisfying the transmit power constraints on the protection implied channel, receiver protection constraints are guaranteed to be met. Any standard single-user or multi-user MIMO precoding scheme may then be performed on the protection-implied channel. When SINR-matching duality-based precoding is applied on the protection-implied channel, sum-capacity under full protection constraints (zero receive power), and near-sum-capacity under partial protection constraints (limited non-zero receive power) are achieved, and were verified by simulations.