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 realize dynamic spectrum access (DSA), spectrum sensing is performed to detect the presence or absence of primary users (PUs). This paper proposes a sensing architecture. This architecture enables use cases such as DSA with PU detection using a single spectrum sensor and DSA with distributed sensing, such as cooperative sensing, collaborative sensing, and selective sensing. In this paper we focus on distributed sensing. These sensing schemes employ distributed spectrum sensors (DSSs) where each sensor uses energy detection (ED) in Rayleigh fading environment. To theoretically analyze the performance of the three sensing schemes, a closed-form expression for the probability of detection by ED with selective combining (SC) in Rayleigh fading environment is derived. Applying this expression to the PU detection problem, we obtain analytical models of the three sensing schemes. Analysis shows that at 5-dB signal-to-noise ratio (SNR) and with a false alarm rate of 0.004, the probability of detection is increased from 0.02 to 0.3 and 0.4, respectively, by cooperative sensing and collaborative sensing schemes using using three DSSs. Results also show that the selected sensing scheme matches the performance of the collaborative sensing scheme. Moreover, it provides a low false alarm rate.

Spectrum sensing is one of the methods to identify available white spaces for secondary usage which was specified by the regulators. However, signal quality to be sensed can plunge to a very low signal-to-noise-ratio due to signal propagation and hence readings from individual sensors will be unreliable. Distributed sensing by the cooperation of multiple sensors is one way to cope with this problem because the diversity gain due to the combining effect of data captured at different position will assist in detecting signals that might otherwise not be detected by a single sensor. In effect, the probability of detection can be improved. We have implemented a distributed sensing system to evaluate the performance of different cooperative sensing algorithms. In this paper we describe our implementation and measurement experience which include the system design, specification of the system, measurement method, the issues and solutions. This paper also confirms the performance enhancement offered by distributed sensing algorithms, and describes several ideas for further enhancement of the sensing quality.

Due to the advancement of software radio and RF technology, cognitive radio(CR) has become an enabling technology to realize dynamic spectrum access through its spectrum sensing and reconfiguration capability. Robust and reliable spectrum sensing is a key factor to discover spectrum opportunity. Single cognitive radios often fail to provide such reliable information because of their inherent sensitivity limitation. Primary signals that are subject to detection by cognitive radios may become weak due to several factors such as fading and shadowing. One approach to overcome this problem is to perform spectrum sensing by using multiple CRs or multiple spectrum sensors. This approach is known as distributed sensing because sensing is carried out through cooperation of spatially distributed sensors. In distributed sensing, sensors should perform spectrum sensing and forward the result to a destination where data fusion is carried out. Depending on the channel conditions between sensors (sensor-to-sensor channel) and between the sensor and the radio (user-channel), we explore different spectrum sensing algorithms where sensors provide the sensing information either cooperatively or independently. Moreover we investigate sensing schemes based on soft information combining (SC), hard information combining (HC). Finally we propose a two-stage detection scheme that uses both SC and HC. The newly proposed detection scheme is shown to provide improved performance compared to sensing based on either HC or SC alone. Computer simulation results are provided to illustrate the performances of the different sensing algorithms.

In distributed spectrum sensing, spatially distributed sensors perform radio frequency (RF) sensing and forward the result to a fusion center (FC). Cognitive radio (CR) obtains spectral information from the FC. Distributed spectrum sensing facilitates reliable discovery of spectrum opportunity while providing enhanced protection to legacy systems. The overall performance of distributed spectrum sensing depends both on the quality of sensing at the individual sensors and the forwarding scheme from the individual sensors. In this aspect the choice of media access control (MAC) plays a significant role. We can improve the system performance by optimizing the MAC and the spectrum sensing parameters jointly. In this paper we propose an enhanced MAC scheme based on existing scheduled MAC protocols to yield a high performance distributed spectrum sensing. To demonstrate our idea, we provide computer simulation by considering energy detection based distributed spectrum sensors and IEEE 802.15.4 PHY and MAC parameters.

This paper presents the efficiency of a sensing database and caching (SDB) for cognitive radio systems. The proposed SDB stores regulatory information from regulatory databases, and contains sensing information by distributed sensing schemes. Preliminary information processing for instance indexing, sorting, or applying some models or algorithms, etc. can be performed for the stored data. Available information and the results of the information processing are provided to cognitive radios in order to determine available spectrum and to facilitate dynamic spectrum access at lower sensing cost but higher sensing quality. The SDB is implemented in local networks, therefore information exchange between SDB and the cognitive radios can be realized at low latency and the amount of signaling traffic to global network can be reduced. This paper analyzes the effect of SDB and the performance evaluation was done in a certain condition. As a result, by deploying SDB a system can achieve up to 20% of reduction of sensing activities and maximum 1.3 times higher sensing quality.