Zheng Zhou

Improved ant routing algorithm in cognitive radio networks

Cognitive radio (CR) is a revolution in radio technology. Cognitive radio networks (CRN) is featured by the dynamic spectrum sharing of the secondary nodes coexisting with the primary nodes. Secondary nodes in cognitive radio networks (CRN) need the ability to work on different frequency bands and intelligently adjust their configuration to changes in the communication environment. It is a complicated and challenge task. So the routing protocol of CRN is different from that of traditional wireless network. In this paper, we propose a new routing protocol which does not need common control channel in CRN. This scheme applies swarm intelligence into CRN routing protocol. It can find out the route , which has minimum delay from source to destination , utilizing a routing cost function. The cost function takes into account many kinds of delay simultaneously. Simulation result shows that the proposed routing algorithm can effectively reduce the cumulate delay.

An Optimal Soft Fusion Scheme for Cooperative Spectrum Sensing in Cognitive Radio Network

This paper proposes an optimal soft fusion scheme for cooperative spectrum sensing in cognitive radio (CR) network. Multiple cooperative secondary users (SUs) simply serve as relay nodes in the network to provide space diversity for spectrum sensing. An optimal soft fusion scheme of the relayed sensing observations is derived in Neyman-Pearson framework, on the basis of maximizing the deflection coefficient of the global test statistic at the fusion center. However, the proposed fusion scheme requires instantaneous measurements of the received PU signal strengths in SUs with high accuracy, which are extremely difficult to obtain in an energy detection based spectrum sensing scenario. An iterative algorithm is therefore proposed to perform the estimation of the received PU signal strengths. Simulation results illustrate that the proposed optimal soft fusion scheme can significantly improve the spectrum sensing performance and the estimate algorithm can effectively approach the ideal performance of the proposed optimal fusion scheme.

User clusters based hierarchical cooperative spectrum sensing in cognitive radio networks

This paper investigates secondary user clusters based cooperative spectrum sensing. Secondary users in the cognitive radio network are grouped into multiple clusters and the cooperative spectrum sensing is performed on a hierarchical architecture of these user clusters, through two levels of user collaborations. The low level cooperation is carried out within each cluster while the high level one is accomplished inside the cluster of the clusterheads. We propose soft fusion and hard fusion according to the bandwidth constraints of the control channels and the spectrum sensing agility requirement. An optimal soft fusion scheme and a double-threshold strategy are proposed to improve the overall spectrum sensing performance in soft fusion and hard fusion, respectively. Analysis and simulations verify that the proposed hierarchical cooperative spectrum sensing schemes can significantly improve the spectrum sensing performance.

Spectrum sense utilizing multi-antenna beams scanning in cognitive radio networks

Spectrum sensing is one of the most important functions for cognitive radio. The performance of some sensing techniques like energy detection is determined by receiving signal to noise ratio (SNR). We applies antenna array using multiple beams to primary user detection. Whole space around cognitive user is divided into several subspaces for multiple beams. The directional beam can improve spectrum sensing performance by increasing receiving SNR. Moreover the approximate direction information of primary user can also be acquired after sensing. The beamformer used here doesnt require channel information and is pre-specified without much computation. The mathematic analysis is given for energy detection using directional beam under different channels. The simulation results prove the performance promotion.

An efficient power allocation scheme in joint spectrum overlay and underlay cognitive radio networks

In this paper, we propose an efficient power allocation scheme that aims at maximizing the system throughput in joint spectrum overlay and underlay cognitive radio network. We show that our proposed scheme enlarges the achievable throughput region comparing to the overlay strategy, and causes less interference than the underlay strategy. In addition, since the unlicensed users adopting the overlay strategy do not necessarily have perfect sensing knowledge regarding the licensee, we modify the power allocation scheme with the imperfect sensing knowledge. The simulation results show that the proposed scheme can achieve better performances.

Accurate blind spectrum sensing based on high order statistical analysis in cognitive radio system

In cognitive radio system, the licensed spectrum resource that is not been used by the primary users could be reused opportunistically by the unlicensed secondary users. Spectrum sensing is the fundamental task in cognitive radio system for the secondary system should detect the available idle spectrum resource accurately and timely. Performance of traditional blind spectrum sensing is limited by the channel fading and noise uncertainty, especially under low SNR environment. Based on the Gaussian Noise suppression feature of high order statistical analysis, a novel spectrum sensing approach is provided based on the simplified Bispectrum slide analysis. Simulations have shown that our approach performs much better than the commonly used energy detector in noisy environment with little more complexity, and the sensing technology is quite appropriate to detect the wireless broadcast TV signal and wireless microphone signals under low SNR environment.

Detection and avoidance scheme for direct-sequence ultra-wideband system: a step towards cognitive radio

Detection and avoidance (DAA) is a soft-spectrum-based adaptation scheme proposed for multi-band ultra-wideband (MB-UWB) radio as a measure of co-existence between UWB devices and existing radio systems in overlapped bands. However, the principle of DAA in the direct-sequence UWB (DS-UWB) is very different from that in MB-UWB method. In DS-UWB, re-design of transmission pulses is required each time a new set of allowed bandwidths is discovered, as opposed to the turning-off-carrier-tone way in MB-UWB. Therefore the re-design of DS-UWB pulses in a cognitive radio environment must be easily reconfigurable. The problem of synthesising DS-UWB pulses conforming to arbitrary spectrum masks is addressed. In the proposed method, the masks are expanded by orthonormal functions chosen to be Hermite-Gaussian functions (HGFs). As the HGFs are eigenfunctions to the fractional Fourier transform, of which the inverse Fourier transform is a particular case, the set of the HGFs constitutes both a time-domain and a frequency-domain basis, that is, a co-basis, and therefore the transmission pulses can be easily obtained from the expansion of the specified spectrum masks. The co-basis-expansion-based DAA scheme for DS-UWB is evaluated through computer simulations.

A cooperative cognitive radio network using smart antenna

In this paper, a cooperative communication scheme using smart antenna is proposed for cognitive radio networks. This scheme expands the concept of cognitive radio in time and space. Using the cooperation, spectrum sensing accuracy and throughput of cognitive radio networks can be observably increased. The licensed users detection and unlicensed users transmission are almost carried on simultaneously. The beamforming of smart antenna can help cognitive radio networks to reduce the interference to licensed users and acquire antenna array gain for unlicensed users. The performance characterizations reveal that the scheme has lower outage probability and more accurate primary detection than general CR networks.

Improved Consecutive Mean Excision Algorithm Based Spectrum Sensing for Dynamic Spectrum Access

This paper deals with spectrum sensing for dynamic spectrum access (DSA) via channelized radiometers. Consecutive mean excision (CME) algorithms have been employed in the literature to identify the presence or absence of licensed user signals. To obtain better control of false-alarm rate and detection rate, an improved CME algorithm is proposed in this paper, in which two thresholds are incorporated to perform the channel cluster based licensed user signal detection. It is verified through numerical experiments that with appropriate compromise on setting the two thresholds, the improved CME algorithm can significantly boost the detection rate while ideally maintain the false-alarm rate as sufficiently low as desired.

An Integration Optimized UWB Transmitted Reference System Based on Wavelet Denoising

This paper exploits the localization property of the wavelet transform to optimize the integration interval in transmitted reference (TR) system. The average correlation receiver is adopted in this paper to suppress the noise contained in the reference signal. The integration time optimization is based on the fact that the path energy decreases as the path delay increases and the tail of a frame time is dominated by noise, consequently, it is unnecessary for the correlation receiver to integrate over the full frame time. Hence, we apply the wavelet transform to locate the energy concentrated area and to optimize the integration time. It consists of two steps: the first one is the wavelet denoising which can intensify the signal part and reduce the noise component; the second one is to estimate the mean and covariance of multipath delay. Simulation results show that the approach performs better than the conventional TR and averaging only approach