Wenshan Yin

Delay and Throughput Oriented Continuous Spectrum Sensing Schemes in Cognitive Radio Networks

Periodic spectrum sensing over the entire primary user (PU) band always interrupts the secondary user (SU) data transmission in the sensing interval, which may degrade the quality of service of the SU. To alleviate this problem, we divide the PU band into two subbands, one for opportunistic SU data transmission, and the other for continuous spectrum sensing. Based on the PU band division, we propose a delay oriented continuous spectrum sensing (DO-CSS) scheme for delay sensitive SU services. In the DO-CSS scheme, the average SU transmission delay is reduced by selecting the proper bandwidth for spectrum sensing within each frame. Since different SUs may have different requirements on their quality of services, we further propose a throughput oriented continuous spectrum sensing (TO-CSS) scheme. In the TO-CSS scheme, the achievable average SU throughput is maximized by choosing the optimal sensing bandwidth within multiple adjacent frames. Both theoretical analyses and simulation results show that compared with the conventional periodical spectrum sensing scheme, the average transmission delay of the SU is reduced without degradation in the maximum achievable throughput by using the proposed DO-CSS scheme, and both the delay performance and achievable SU throughput are further improved by using the proposed TO-CSS scheme.

Joint Sensing and Transmission for AF Relay Assisted PU Transmission in Cognitive Radio Networks

Recent measurements show that there are abundant spectrum opportunities across the licensed cellular bands, over which the relay stations (RSs) are widely employed for both coverage extension and throughput improvement. However, current efforts in cognitive radios focus on exploiting spectrum holes over the licensed direct transmission links. To exploit new spectrum opportunities over the licensed relay assisted transmission links, we propose a novel two-phase joint sensing and transmission scheme (TP-JSTS) for the dual-hop Amplify-and-Forward (AF) relay assisted primary user (PU) transmission in cognitive radio networks. The TP-JSTS takes into account the relay behaviors of the PU system. In the first phase, the secondary user (SU) senses the signal transmitted by the PU base station (BS). In the second phase, the SU detects the signals sent by the PU-Relays. To protect the PU from harmful interference, the SU transmits within the current band in the rest of each phase only when the PU is detected to be absent. We investigate the sensing performance, throughput performance and delay performance of our proposed TP-JSTS when all the PU-Relays adopt the AF relay protocol. We obtain the optimal sensing-time allocation strategy that maximizes the achievable throughput of the SU and the optimal sensing-time allocation strategy that minimizes the average transmission delay of the SU. Simulation results show that there exists an optimal pair of sensing-time durations that maximizes the achievable throughput for the SU, while there exists another optimal pair of sensing-time durations that minimizes the average transmission delay for the SU.

Performance of energy detector in the presence of noise uncertainty in cognitive radio networks

Energy detector is simple in structure and easy to implement. Therefore, it is a promising candidate for spectrum sensing in cognitive radio networks. However, its detection performance is typically challenged by the noise uncertainty. Thus, the detection performance of energy detector in the presence of noise uncertainty needs to be evaluated. In this paper, we derive the decision rules for the energy detector in the presence of noise uncertainty by employing a widely used model. Firstly, we derive the decision rule for unknown deterministic signal when the noise power is uncertain. Second, we derive the decision rule for random Gaussian distributed signal when there is noise uncertainty. Then, we analyze the detection performance of the energy detector in the presence of noise uncertainty for both unknown deterministic signal and random Gaussian distributed signal. Both theoretical analyses and simulation results show that in the presence of noise uncertainty, our derived decision rules provide precise sensing thresholds for the energy detector. Furthermore, compared with the conventional decision rule obtained by overestimating the noise power, our decision rules provide performance gains in terms of signal to noise ratio.

A Joint Sensing-Time Adaption and Data Transmission Scheme in Cognitive Radio Networks

Spectrum sensing is performed by secondary users (SUs) to detect primary users (PUs) in cognitive radio networks. The limited time duration allocated for spectrum sensing may result in high false alarm probability, which always leads to low spectrum utilization and degrades the SU throughput. To overcome this problem, we propose a novel joint sensingtime adaption and data transmission (JSTA-DT) scheme. In our proposed JSTA-DT scheme, two adjacent sensing periods are bundled to form a sensing block. In each sensing block, the SU performs partial time spectrum sensing in the first sensing period. If the sensing result indicates that the PU is absent, the SU transmits its data; otherwise, the SU performs full time spectrum sensing adaptively. Both theoretical analyses and simulation results show that compared to the conventional partial time spectrum sensing and data transmission scheme, the spectrum utilization and achievable SU throughput are improved significantly by using our proposed JSTA-DT scheme.

A pilot-aided detector for spectrum sensing of Digital Video Broadcasting—Terrestrial signals in cognitive radio networks

In this paper, the main properties of digital television broadcasting signals based on the Digital Video Broadcasting—Terrestrial (DVB-T) standard are analyzed, and these properties are utilized to design a new pilot-aided detector for spectrum sensing in cognitive radio networks. The proposed detector consists of a processing unit and a combination and decision unit. In the processing unit, multiple statistics that correspond to different enhanced pilot components are computed. In the combination and decision unit, three newly proposed combination schemes are adopted to combine these statistics, and then, a final decision on the presence or absence of the DVB-T signals is made on the basis of the Neyman–Pearson criterion. The proposed pilot-aided detector exploits both the periodic continual and scattered pilots that are intrinsic in the DVB-T signals, processes the observed data timely, experiences short sensing duration, and requires no time synchronization information. Furthermore, the proposed pilot-aided detector is able to distinguish DVB-T signals from interference. Theoretical analysis and simulation results show that spectrum bands that are not currently occupied by the DVB-T systems can be detected accurately by using the proposed pilot-aided detector. Simulation results also demonstrate the significant performance gain of the proposed detector compared with the counterparts.Copyright

A Suboptimal Sensing Scheme for OFDM Signal Based on Pilots Estimation in Cognitive Radios

The optimal detector for CP (Cyclic Prefix)-OFDM (Orthogonal Frequency Division Multiplexing) signal with inherent periodic pilots in low signal to noise ratio environments relies on perfect time synchronization. In this paper, we modify the optimal detector and propose a new suboptimal sensing scheme based on pilots estimation (SSS-BPE). In the proposed SSS-BPE, the likelihood criterion and periodicity of the pilot components are utilized to estimate the pilots. The estimated pilots together with the modified optimal sensing scheme are then utilized to detect the primary user signal based on the Neyman-Pearson Criterion. The proposed SSS-BPE efficiently exploits typical features in the CP-OFDM signal with no requirement on time synchronization information, and is able to distinguish between the primary user signal and interference. Theoretical analysis and simulation results show that the proposed scheme can effectively and reliably detect the presence of spectrum bands that are not used by the primary users. Furthermore, the computational complexity of the proposed SSS-BPE is relatively low compared to the counterparts.

Cognitive AF Relay Schemes for Uplink Transmission in Macrocellular Networks

Cognitive radio has been proposed to improve the spectrum utilization by allowing the unlicensed secondary users (SUs) to access the spectrum resources licensed to the primary users (PUs) opportunistically. However, the cognitive radio has rarely been employed to enhance the system performance of the licensed PUs that endure spectrum scarcity. To improve the outage-probability quality-of-service (QoS) of the mobile station (MS) in macrocellular networks, we propose two Cognitive Amplify-and-forward Relay (CAR) schemes in this paper. In our proposed CAR schemes, the MS and relay utilize both the licensed spectrum band (LSB) provided to the macrocellular network and the opportunistic spectrum band (OSB) discovered by the base stations. Simulation results show that compared with the conventional transmission schemes without cognitive relay, our proposals can effectively improve the outage performance of MS in macrocellular networks by exploiting both the space diversity and spectrum diversity.

Throughput and Sensing Bandwidth Tradeoff in Cognitive Radio Networks

Within the sequential sensing and transmission paradigm (SSTP), spectrum sensing over the whole primary user (PU) band always suspends secondary user (SU) data transmission in the sensing interval. Delay incurred by this kind of suspension may be intolerable to delay sensitive SU services. To alleviate this problem, we adopt a parallel sensing and transmission paradigm (PSTP), within which the SU transmits and senses simultaneously. In this paper, we investigate the relationship between the achievable SU throughput and bandwidth allocated for spectrum sensing within the PSTP, under the constraint that the PU is sufficiently protected. We also study the delay improvements of the PSTP over that of the SSTP. Both theoretical analyses and simulation results that there exists an optimal sensing bandwidth that maximizes the achievable SU throughput within the PSTP. Furthermore, compared to the SSTP, the SU delay is reduced by using the PSTP.

Reduced-Rank Equalization of Unitary Multistage Wiener Filter Based on Rectangle Blocking Matrix for Multiple Input Multiple Output

Traditional equalization algorithms for Multiple Input Multiple Output (MIMO) Systems suffer from high complexity and low convergence rate. So its necessary to develop an equalization algorithm to minimize the computational complexity and improve the convergence rate. This paper presents a new adaptive reduced-rank linear equalization algorithm, called Rectangle Unitary MultistageWiener Filter Reduced-Rank Equalization (RUMSWFRE). In the equalization process, the rectangle blocking matrix is utilized by Multistage Wiener Filter and implemented by the Correlation Subtraction Algorithm. The new scheme uses a rectangle blocking matrix, which is chosen from the square blocking matrix of Unitary Multistage Wiener Filter (UMSWF). And it can reduce the size of observation data vectors step by step in the forward recursion decomposition of UMSWF. In this way, the computational complexity is reduced and the convergence rate becomes faster. Performance analysis and simulation results show that this proposed method yields similar error performance with much lower computational complexity and faster convergence rate compared with the traditional ones.