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Bayesian Compressive Sensing (BCS), introduced into wideband cognitive radio network (CRN), has been considered as a promising technique for its ability of accurately recovering a signal from far fewer samples than required by the Nyquist sampling theorem. However, as BCS algorithm modulates the number of measurements step by step through evaluating the error bars, it needs appreciable amounts of...
Compressed sensing-based wideband spectrum sensing approaches have gotten much attention owning to their advantage of relieving the pressure on high signal acquisition costs. Most of these approaches need to recover the signal or power spectrum, which require high computational complexity. This letter proposes a novel wideband sensing algorithm with no recovery (NoR) of spectral, where the location...
In cooperative spectrum sensing, malicious user (MU) sends tampered sensing result in spectrum sensing to pose threats to cognitive radio networks, which is called spectrum sensing data falsification (SSDF) attack. Many existing MU detection schemes are designed for the narrow-band environment. However, Research on MU detection schemes for compressive sensing (CS), which has some huge advantages in...
Cooperative spectrum sensing schemes can enable cognitive radio (CR) users to efficiently identify the unoccupied channels or spectrum holes, as well as overcome the impact of shadowing and fading. Considering the hardware limitation, compressive sensing (CS) is a solution scheme to alleviate the requirements on the receiver hardware, which can recover the wideband sparse signal sampled at sub-Nyquist...
Bayesian Compressive Sensing (BCS) can effectively relax the requirement of hardware operational bandwidth and perfectly recover sparse wideband signal at sub-Nyquist rate in wideband spectrum sensing. However, one of the problem of BCS is the long recovery time caused by the high computational complexity. In this paper, a PU Probability Prediction based Bayesian Compressive Sensing algorithm (PBCS)...
In order to reduce sampling costs and computational complexity in the signal reconstruction process of existing compressed spectrum sensing (CSS), we propose a novel two-step compressed spectrum sensing (TS-CSS) scheme exploiting correlation of occupation states between sensing periods. At the first step of TS-CSS, we detect busy sub-channels of last sensing period to find the sub-channels that are...
In overlay cognitive radio network, the available spectrum for secondary users are dynamically grabbed from a wideband of hundreds megahertz by spectrum sensing, which leads to remarkably differential path loss among different frequencies according to propagation theory. Adjusting the global path loss of cognitive relay system through spectrum allocation can serve nontrivial increment to the performance...
Compressed spectrum sensing (CSS) is proposed to detect spectrum opportunities efficiently over a wideband. However, most of existing CSS approaches will cause high computation costs for signal recovery when spectrum bandwidth goes large. As a result, it prolongs time for spectrum detection, which however runs counter to the original purpose of finding out spectrum opportunities over a wideband as...
In wideband compressive spectrum sensing, when the number of occupied subbands in the monitored wideband increases, the existing compressive sensing approaches have to raise the sampling rate to maintain a desired sensing performance. What is worse, that will add computational complexity of the following signal reconstruction. To overcome this issue, this paper proposes a novel wideband spectrum sensing...
In the existing distributed cooperative spectrum sensing schemes, cooperation based on consensus algorithms is a research hotspot. However, the existing methods haven't embodied the reliability difference among cognitive radio users, so there is an enormous scope to improve the accuracy. In this paper, we propose a weighted average consensus-based distributed compressive spectrum sensing (PE-WDCS)...
By using Relevance Vector Machine (RVM) to solve the problem of sparse signal recovery, Bayesian Compressive Sensing (BCS) can obtain good performance in spectral discrete spike signal detection. However, in cognitive radio (CR) system, the spectrum of primary user's signal, which is continuous in narrowband and is block sparse in wideband, cannot be exactly recovered by BCS. In this paper, a Bayesian...
The energy consumption driven by dramatic growing demand for mobile data rates has attracted extensive attention. It is expected that the next generation cellular communication systems should improve not only spectral efficiency but also energy efficiency. Coordinated multi-point transmission (CoMP) and heterogeneous networks (HetNets) are two techniques for achieving high spectral efficiency and...
In the Long Term Evolution system, Discontinuous Transmission and Reception (DRX/DTX) has been introduced to extend the terminal battery lifetime. In this paper, we research the power-saving provided by our proposed mechanism and the impact on the system performance under the dynamic scheduling joint the delivery of unicast and E-MBMS services. The simulation results show that this mechanism can increase...
In cellular networks, multiple relay nodes can be deployed in one cell, so there are three transmission modes, direct transmission (DT), two-hop transmission (TT) and cooperative transmission (CT). Combining with the node sleeping method for power saving, different transmission modes will have different energy efficiency for different user equipment (UE). In this paper, a self-adaptive energy efficient...
Currently, how to achieve a flexible RF front-end of cognitive radio becomes a research hotspot. Cognitive user receives the wideband signal which contains the unwanted signals, and suffers from the issue that LO harmonics will down-convert the unwanted signals to the baseband along with the desired baseband signal. In this paper, we propose a novel Adjustable Harmonic Rejection Mixer (AHRM) which...
In this paper, A power-saving scheduling algorithm (PSA) for mixed multicast and unicast traffic is proposed in multicast and broadcast single frequency network (MBSFN). This algorithm is designed on the purpose of reducing the terminal's energy consumption and improving system capacity. By MBSFN area scheduling scheme the throughput of multicast users is increased. And the users' energy consumption...
In this paper, we propose a spectrum detection algorithm based on an orthogonal dual-polarized antenna for cognitive radio, called polarization spectrum detection. In the proposed algorithm, using polarization information from dual-polarization received antenna, the test statistic is derived according to likelihood ratio test criteria, and is compared with threshold to detect whether the primary user...
In this paper, we employ to provide a method which combines Turbo codes and Low-Density Parity-Check (LDPC) codes based on Orthogonal Frequency Division Multiplexing (OFDM) system by adaptive encoding. The technique of channel estimation is used. The code rate and encoding scheme are all adaptive selection in the light of different channel conditions, so that we can make good use of these two types...
One key characteristic of mobile wireless communication is the typically rapid and significant variations in the instantaneous channel conditions. So, precise channel estimation and signal detection algorithm with low computational complexity at the receiver is very important and necessary. In this paper, linear Minimum Mean Square Error (MMSE) and Maximum Likelihood (ML) detection methods in MIMO-OFDM...
Scheduling algorithms for quality of service (QoS) are of utmost importance in WiMAX network. The IEEE 802.16 standard provides a framework for the scheduling mechanisms, but details for implementation of scheduling algorithms are unspecified. In this paper, we propose an efficient and integrated uplink scheduling algorithm. Our research is based on point-to-multipoint (PMP) architecture; also a resource...
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