We proposed two methods for the localization of drone controllers based on received signal streng... more We proposed two methods for the localization of drone controllers based on received signal strength indicator (RSSI) ratios: the RSSI ratio fingerprint method and the model-based RSSI ratio algorithm. To evaluate the performance of our proposed algorithms, we conducted both simulations and field trials. The simulation results show that our two proposed RSSI-ratio-based localization methods outperformed the distance mapping algorithm proposed in literature when tested in a WLAN channel. Moreover, increasing the number of sensors improved the localization performance. Averaging a number of RSSI ratio samples also improved the performance in propagation channels that did not exhibit location-dependent fading effects. However, in channels with location-dependent fading effects, averaging a number of RSSI ratio samples did not significantly improve the localization performance. Additionally, reducing the grid size improved the performance in channels with small shadowing factor values, b...
Since atomically thin two-dimensional (2D) graphene was successfully synthesized in 2004, it has ... more Since atomically thin two-dimensional (2D) graphene was successfully synthesized in 2004, it has garnered considerable interest due to its advanced properties. However, the weak optical absorption and zero bandgap strictly limit its further development in optoelectronic applications. In this regard, other 2D materials, including black phosphorus (BP), transition metal dichalcogenides (TMDCs), 2D Te nanoflakes, and so forth, possess advantage properties, such as tunable bandgap, high carrier mobility, ultra-broadband optical absorption, and response, enable 2D materials to hold great potential for next-generation optoelectronic devices, in particular, mid-infrared (MIR) band, which has attracted much attention due to its intensive applications, such as target acquisition, remote sensing, optical communication, and night vision. Motivated by this, this article will focus on the recent progress of semiconducting 2D materials in MIR optoelectronic devices that present a suitable categor...
2000 10th European Signal Processing Conference, 2000
Prime factor fast algorithms are computationally efficient for various discrete transforms. Howev... more Prime factor fast algorithms are computationally efficient for various discrete transforms. However, they generally need an index mapping process to convert one-dimensional input sequence into a two-dimensional array, which results in a substantially computational overhead and an irregular computational structure. This letter attempts to minimize the computation overhead by a simple and general mapping procedure.
In recent years, software defined radio and digital signal processing have been widely used in co... more In recent years, software defined radio and digital signal processing have been widely used in communication and radar. As a result, the hardware and RF front-end for radar and wireless communication tends to be similar. Thus, using the same RF and hardware platform for joint radar-communication becomes viable. Joint radar-communication would bring more efficient plan and usage for the radio spectral resource. Furthermore, it could enable new applications that require information exchange and precise localization at the same time. In this paper, cyclic prefixed single carrier (CP-SC) and its variations are chosen as the waveforms for joint radar-communication. CP-SC waveform and its variations are popular in wireless communication and have been chosen by a few standards like IEEE 802.11ad and LTE-advanced. Efficient algorithms are proposed to use such waveforms for range and speed detection/estimation of targets. The proposed algorithms are derived from the maximum likelihood (ML) principle and have low computational complexity. Simulations show that the estimation performance of the proposed method is almost the same as that of ML and is much better than that of the channel estimation based method.
Fourth International Conference on Information, Communications and Signal Processing, 2003 and the Fourth Pacific Rim Conference on Multimedia. Proceedings of the 2003 Joint
Sulspaee method is well-known in C D M A channel estimation. But a basic problem, channel identi-... more Sulspaee method is well-known in C D M A channel estimation. But a basic problem, channel identi-6abdllty by submethod, is stiU not well-solwd. In this paper, tano subpacs based bUnd method= far estimat-the channel ~esponses ofa OFDM-CDMA Bystem in downllnlr and uplink are discussed res@ively. Under some rOQSOnable assumptions, it is mathematieally proved that subpace method for downlink can estimate the channel smbjbiect to a soalar ambiguity, and the method for uplink can g h the channel rea-subJ& to a dhgonal matrix amhapity. The methods do not need predse channel order information (d y an upper bound for the d e r s is required). Simulations shov that the methods are effective and robust.
2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN), 2010
This paper is interested in spectrum sensing using multiple antennas under spatially and temporal... more This paper is interested in spectrum sensing using multiple antennas under spatially and temporally correlated noise environments. We exploit cyclostationary features of the primary user's signal in terms of cyclic spectral coherence function and the proposed modified cyclic spectral density function, which has less computational complexity. Two types of detectors are proposed: pre-combining and post-combining detectors. For precombining method, a blind maximum ratio combining technique is considered. All detectors are designed to handle noise uncertainty and also be effective in both white noise and colored noise scenarios. Numerical results are given to illustrate the performance of all detectors and verify their efficiency against the noise correlation effect. With the use of estimated channels, precombining detectors are superior to post-combining detectors, which do not require channel information. It is also shown that the modified cyclic spectral density function achieves comparable performance to the cyclic spectral coherence function.
2009 IEEE 20th International Symposium on Personal, Indoor and Mobile Radio Communications, 2009
The problem of multiuser cooperation to achieve cooperative diversity for single-antenna terminal... more The problem of multiuser cooperation to achieve cooperative diversity for single-antenna terminals is considered. A cooperative strategy is proposed which divides multiple users into groups with each group having two users as partners. The two users alternately transmit their own information first, then simultaneously amplify and forward the partner's data in the same channel. Comparing to the conventional multiuser cooperation where the two users relay the partner's data in two orthogonal channels, the spectral efficiency of the proposed scheme is increased. However, as the two users relay the partner's data in the same channel, multiuser detection problem arises. An iterative detection making use of the new scheme's property is proposed in the presence of frequency offsets. The proposed scheme only requires time and frequency synchronization but no channel state information at the user terminals. To estimate the channel at the destination, a training scheme is proposed. The simulation results show that the proposed scheme can achieve the same cooperative diversity as the conventional scheme, while the spectral efficiency is lifted by 4/3.
2008 IEEE International Conference on Communications, 2008
Channel sensing, i.e., detecting the presence of primary users, is a fundamental problem in cogni... more Channel sensing, i.e., detecting the presence of primary users, is a fundamental problem in cognitive radio. Energy detection is optimal for detecting independent and identically distributed (iid) signals, but not optimal for detecting correlated signals. In this paper, a method is proposed based on the sample covariance matrix calculated from a limited number of received signal samples. The maximum eigenvalue of the sample covariance matrix is used as the test statistic. Since the covariance matrix catches the correlations among the signal samples, the proposed method is better than the energy detection for correlated signals. For iid signals, the method approaches to the energy detection. The random matrix theory is used to analyze the method and set the threshold. Similar to energy detection, the methods do not need any information of the source signal and the channel as a priori. Also, no synchronization is needed. Simulations based on wireless microphone signals and iid signals are presented to verify the method.
2010 IEEE Global Telecommunications Conference GLOBECOM 2010, 2010
In recent years, some spectrum sensing algorithms using multiple antennas, such as the eigenvalue... more In recent years, some spectrum sensing algorithms using multiple antennas, such as the eigenvalue based detection (EBD), have attracted a lot of attention. In this paper, we are interested in deriving the asymptotic distributions of the test statistics of the EBD algorithms. Two EBD algorithms using sample covariance matrices are considered: maximum eigenvalue detection (MED) and condition number detection (CND). The earlier studies usually assume that the number of antennas (K) and the number of samples (N) are both large, thus random matrix theory (RMT) can be used to derive the asymptotic distributions of the maximum and minimum eigenvalues of the sample covariance matrices. While assuming the number of antennas being large simplifies the derivations, in practice, the number of antennas equipped at a single secondary user is usually small, say 2 or 3, and once designed, this antenna number is fixed. Thus in this paper, our objective is to derive the asymptotic distributions of the eigenvalues and condition numbers of the sample covariance matrices for any fixed K but large N , from which the probability of detection and probability of false alarm can be obtained. The proposed methodology can also be used to analyze the performance of other EBD algorithms. Finally, computer simulations are presented to validate the accuracy of the derived results.
IEEE International Conference on Communications, 2005. ICC 2005. 2005
Many known second-order statistics based blind algorithms for MIMO channel estimation are sensiti... more Many known second-order statistics based blind algorithms for MIMO channel estimation are sensitive to channel order overestimations. To overcome this problem, an algorithm is proposed in [1] for SIMO system only, and then a simple generalization of it to MIMO system is presented in [2]. In this paper, improvements and refinements on the algorithm in [2] are given, which makes the method robust to noise and round-off error. The method can give estimations of all channel impulse responses subject to a scalar matrix ambiguity when only an upper bound for all MIMO channel orders is known.
A phosphorescent probe based on a long-lived iridium(iii) complex has been developed for time-res... more A phosphorescent probe based on a long-lived iridium(iii) complex has been developed for time-resolved CO2gas identification with high selectivity and photostability.
Radar Signal Processing and Its Applications, 2003
We first show that for some kinds of signals a ''bandwidth and time duration reduction technique'... more We first show that for some kinds of signals a ''bandwidth and time duration reduction technique'' can be used to simulate waveform distortions caused by moving targets, that is, it is correct to measure the waveform distortions at very large TB with relatively small by reducing TB and increasing while keeping TB unchanged, where T is the duration of the transmitted signal, B is the bandwidth and is the relative speed of targets. We then study the waveform distortions in SAR signals caused by moving antenna. Based on the bandwidth and time duration reduction technique, a lot of time and memory are saved in simulations. We then confirm by simulations that waveform distortions do pose problems when processing very large bandwidth and long duration SAR data using conventional SAR processing methods. Finally we propose the concepts of wideband and narrowband processing of SAR data. Models are set up for wideband and narrowband SAR data processing, and new methods are presented for reconstructing targets using the proposed models. Simulations show that the methods can improve the quality of the simulated SAR images.
2010 IEEE International Conference on Communication Systems, 2010
We consider a distributed opportunistic spectrum access (D-OSA) scenario in which multiple cognit... more We consider a distributed opportunistic spectrum access (D-OSA) scenario in which multiple cognitive radio (CR) users attempt to access a channel licensed to some primary network. CR users operate on a frame-by-frame basis and need to carry out spectrum sensing at the beginning of each frame to determine whether the primary network is active or idle. Upon detecting the primary
IEEE Transactions on Wireless Communications, 2013
We survey the performance analysis of the suboptimal detectors in terms of probabilities of detec... more We survey the performance analysis of the suboptimal detectors in terms of probabilities of detection and false alarm, and selection of detection threshold and number of samples. With the prior knowledge that the primary user is highly likely idle and the primary signals are digitally modulated, Here a Bayesian detector (BD) for digitally modulated primary signals to maximize the spectrum utilization, without the prior information on the transmitted sequence of the primary signals is proposed. The proposed method makes use of the prior statistics of PU activity and the signalling information of the PU such as symbol rate and modulation order to improve the SU throughput and the overall spectrum utilization of both PUs and SUs.
IEEE Transactions on Wireless Communications, 2008
In a cognitive radio network, the secondary users are allowed to utilize the frequency bands of p... more In a cognitive radio network, the secondary users are allowed to utilize the frequency bands of primary users when these bands are not currently being used. To support this spectrum reuse functionality, the secondary users are required to sense the radio frequency environment, and once the primary users are found to be active, the secondary users are required to vacate the channel within a certain amount of time. Therefore, spectrum sensing is of significant importance in cognitive radio networks. There are two parameters associated with spectrum sensing: probability of detection and probability of false alarm. The higher the probability of detection, the better the primary users are protected. However, from the secondary users' perspective, the lower the probability of false alarm, the more chances the channel can be reused when it is available, thus the higher the achievable throughput for the secondary network. In this paper, we study the problem of designing the sensing duration to maximize the achievable throughput for the secondary network under the constraint that the primary users are sufficiently protected. We formulate the sensing-throughput tradeoff problem mathematically, and use energy detection sensing scheme to prove that the formulated problem indeed has one optimal sensing time which yields the highest throughput for the secondary network. Cooperative sensing using multiple mini-slots or multiple secondary users are also studied using the methodology proposed in this paper. Computer simulations have shown that for a 6MHz channel, when the frame duration is 100ms, and the signal-tonoise ratio of primary user at the secondary receiver is −20dB, the optimal sensing time achieving the highest throughput while maintaining 90% detection probability is 14.2ms. This optimal sensing time decreases when distributed spectrum sensing is applied.
Spectrum sensing, i.e., detecting the presence of primary users in a licensed spectrum, is a fund... more Spectrum sensing, i.e., detecting the presence of primary users in a licensed spectrum, is a fundamental problem in cognitive radio. Since the statistical covariances of received signal and noise are usually different, they can be used to differentiate the case where the primary user's signal is present from the case where there is only noise. In this paper, spectrum sensing algorithms are proposed based on the sample covariance matrix calculated from a limited number of received signal samples. Two test statistics are then extracted from the sample covariance matrix. A decision on the signal presence is made by comparing the two test statistics. Theoretical analysis for the proposed algorithms is given. Detection probability and associated threshold are found based on statistical theory. The methods do not need any information of the signal, the channel and noise power a priori. Also, no synchronization is needed. Simulations based on narrowband signals, captured digital television (DTV) signals and multiple antenna signals are presented to verify the methods.
Spectrum sensing is a fundamental component is a cognitive radio. In this paper, we propose new s... more Spectrum sensing is a fundamental component is a cognitive radio. In this paper, we propose new sensing methods based on the eigenvalues of the covariance matrix of signals received at the secondary users. In particular, two sensing algorithms are suggested, one is based on the ratio of the maximum eigenvalue to minimum eigenvalue; the other is based on the ratio of the average eigenvalue to minimum eigenvalue. Using some latest random matrix theories (RMT), we quantify the distributions of these ratios and derive the probabilities of false alarm and probabilities of detection for the proposed algorithms. We also find the thresholds of the methods for a given probability of false alarm. The proposed methods overcome the noise uncertainty problem, and can even perform better than the ideal energy detection when the signals to be detected are highly correlated. The methods can be used for various signal detection applications without requiring the knowledge of signal, channel and noise power. Simulations based on randomly generated signals, wireless microphone signals and captured ATSC DTV signals are presented to verify the effectiveness of the proposed methods.
We proposed two methods for the localization of drone controllers based on received signal streng... more We proposed two methods for the localization of drone controllers based on received signal strength indicator (RSSI) ratios: the RSSI ratio fingerprint method and the model-based RSSI ratio algorithm. To evaluate the performance of our proposed algorithms, we conducted both simulations and field trials. The simulation results show that our two proposed RSSI-ratio-based localization methods outperformed the distance mapping algorithm proposed in literature when tested in a WLAN channel. Moreover, increasing the number of sensors improved the localization performance. Averaging a number of RSSI ratio samples also improved the performance in propagation channels that did not exhibit location-dependent fading effects. However, in channels with location-dependent fading effects, averaging a number of RSSI ratio samples did not significantly improve the localization performance. Additionally, reducing the grid size improved the performance in channels with small shadowing factor values, b...
Since atomically thin two-dimensional (2D) graphene was successfully synthesized in 2004, it has ... more Since atomically thin two-dimensional (2D) graphene was successfully synthesized in 2004, it has garnered considerable interest due to its advanced properties. However, the weak optical absorption and zero bandgap strictly limit its further development in optoelectronic applications. In this regard, other 2D materials, including black phosphorus (BP), transition metal dichalcogenides (TMDCs), 2D Te nanoflakes, and so forth, possess advantage properties, such as tunable bandgap, high carrier mobility, ultra-broadband optical absorption, and response, enable 2D materials to hold great potential for next-generation optoelectronic devices, in particular, mid-infrared (MIR) band, which has attracted much attention due to its intensive applications, such as target acquisition, remote sensing, optical communication, and night vision. Motivated by this, this article will focus on the recent progress of semiconducting 2D materials in MIR optoelectronic devices that present a suitable categor...
2000 10th European Signal Processing Conference, 2000
Prime factor fast algorithms are computationally efficient for various discrete transforms. Howev... more Prime factor fast algorithms are computationally efficient for various discrete transforms. However, they generally need an index mapping process to convert one-dimensional input sequence into a two-dimensional array, which results in a substantially computational overhead and an irregular computational structure. This letter attempts to minimize the computation overhead by a simple and general mapping procedure.
In recent years, software defined radio and digital signal processing have been widely used in co... more In recent years, software defined radio and digital signal processing have been widely used in communication and radar. As a result, the hardware and RF front-end for radar and wireless communication tends to be similar. Thus, using the same RF and hardware platform for joint radar-communication becomes viable. Joint radar-communication would bring more efficient plan and usage for the radio spectral resource. Furthermore, it could enable new applications that require information exchange and precise localization at the same time. In this paper, cyclic prefixed single carrier (CP-SC) and its variations are chosen as the waveforms for joint radar-communication. CP-SC waveform and its variations are popular in wireless communication and have been chosen by a few standards like IEEE 802.11ad and LTE-advanced. Efficient algorithms are proposed to use such waveforms for range and speed detection/estimation of targets. The proposed algorithms are derived from the maximum likelihood (ML) principle and have low computational complexity. Simulations show that the estimation performance of the proposed method is almost the same as that of ML and is much better than that of the channel estimation based method.
Fourth International Conference on Information, Communications and Signal Processing, 2003 and the Fourth Pacific Rim Conference on Multimedia. Proceedings of the 2003 Joint
Sulspaee method is well-known in C D M A channel estimation. But a basic problem, channel identi-... more Sulspaee method is well-known in C D M A channel estimation. But a basic problem, channel identi-6abdllty by submethod, is stiU not well-solwd. In this paper, tano subpacs based bUnd method= far estimat-the channel ~esponses ofa OFDM-CDMA Bystem in downllnlr and uplink are discussed res@ively. Under some rOQSOnable assumptions, it is mathematieally proved that subpace method for downlink can estimate the channel smbjbiect to a soalar ambiguity, and the method for uplink can g h the channel rea-subJ& to a dhgonal matrix amhapity. The methods do not need predse channel order information (d y an upper bound for the d e r s is required). Simulations shov that the methods are effective and robust.
2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN), 2010
This paper is interested in spectrum sensing using multiple antennas under spatially and temporal... more This paper is interested in spectrum sensing using multiple antennas under spatially and temporally correlated noise environments. We exploit cyclostationary features of the primary user's signal in terms of cyclic spectral coherence function and the proposed modified cyclic spectral density function, which has less computational complexity. Two types of detectors are proposed: pre-combining and post-combining detectors. For precombining method, a blind maximum ratio combining technique is considered. All detectors are designed to handle noise uncertainty and also be effective in both white noise and colored noise scenarios. Numerical results are given to illustrate the performance of all detectors and verify their efficiency against the noise correlation effect. With the use of estimated channels, precombining detectors are superior to post-combining detectors, which do not require channel information. It is also shown that the modified cyclic spectral density function achieves comparable performance to the cyclic spectral coherence function.
2009 IEEE 20th International Symposium on Personal, Indoor and Mobile Radio Communications, 2009
The problem of multiuser cooperation to achieve cooperative diversity for single-antenna terminal... more The problem of multiuser cooperation to achieve cooperative diversity for single-antenna terminals is considered. A cooperative strategy is proposed which divides multiple users into groups with each group having two users as partners. The two users alternately transmit their own information first, then simultaneously amplify and forward the partner's data in the same channel. Comparing to the conventional multiuser cooperation where the two users relay the partner's data in two orthogonal channels, the spectral efficiency of the proposed scheme is increased. However, as the two users relay the partner's data in the same channel, multiuser detection problem arises. An iterative detection making use of the new scheme's property is proposed in the presence of frequency offsets. The proposed scheme only requires time and frequency synchronization but no channel state information at the user terminals. To estimate the channel at the destination, a training scheme is proposed. The simulation results show that the proposed scheme can achieve the same cooperative diversity as the conventional scheme, while the spectral efficiency is lifted by 4/3.
2008 IEEE International Conference on Communications, 2008
Channel sensing, i.e., detecting the presence of primary users, is a fundamental problem in cogni... more Channel sensing, i.e., detecting the presence of primary users, is a fundamental problem in cognitive radio. Energy detection is optimal for detecting independent and identically distributed (iid) signals, but not optimal for detecting correlated signals. In this paper, a method is proposed based on the sample covariance matrix calculated from a limited number of received signal samples. The maximum eigenvalue of the sample covariance matrix is used as the test statistic. Since the covariance matrix catches the correlations among the signal samples, the proposed method is better than the energy detection for correlated signals. For iid signals, the method approaches to the energy detection. The random matrix theory is used to analyze the method and set the threshold. Similar to energy detection, the methods do not need any information of the source signal and the channel as a priori. Also, no synchronization is needed. Simulations based on wireless microphone signals and iid signals are presented to verify the method.
2010 IEEE Global Telecommunications Conference GLOBECOM 2010, 2010
In recent years, some spectrum sensing algorithms using multiple antennas, such as the eigenvalue... more In recent years, some spectrum sensing algorithms using multiple antennas, such as the eigenvalue based detection (EBD), have attracted a lot of attention. In this paper, we are interested in deriving the asymptotic distributions of the test statistics of the EBD algorithms. Two EBD algorithms using sample covariance matrices are considered: maximum eigenvalue detection (MED) and condition number detection (CND). The earlier studies usually assume that the number of antennas (K) and the number of samples (N) are both large, thus random matrix theory (RMT) can be used to derive the asymptotic distributions of the maximum and minimum eigenvalues of the sample covariance matrices. While assuming the number of antennas being large simplifies the derivations, in practice, the number of antennas equipped at a single secondary user is usually small, say 2 or 3, and once designed, this antenna number is fixed. Thus in this paper, our objective is to derive the asymptotic distributions of the eigenvalues and condition numbers of the sample covariance matrices for any fixed K but large N , from which the probability of detection and probability of false alarm can be obtained. The proposed methodology can also be used to analyze the performance of other EBD algorithms. Finally, computer simulations are presented to validate the accuracy of the derived results.
IEEE International Conference on Communications, 2005. ICC 2005. 2005
Many known second-order statistics based blind algorithms for MIMO channel estimation are sensiti... more Many known second-order statistics based blind algorithms for MIMO channel estimation are sensitive to channel order overestimations. To overcome this problem, an algorithm is proposed in [1] for SIMO system only, and then a simple generalization of it to MIMO system is presented in [2]. In this paper, improvements and refinements on the algorithm in [2] are given, which makes the method robust to noise and round-off error. The method can give estimations of all channel impulse responses subject to a scalar matrix ambiguity when only an upper bound for all MIMO channel orders is known.
A phosphorescent probe based on a long-lived iridium(iii) complex has been developed for time-res... more A phosphorescent probe based on a long-lived iridium(iii) complex has been developed for time-resolved CO2gas identification with high selectivity and photostability.
Radar Signal Processing and Its Applications, 2003
We first show that for some kinds of signals a ''bandwidth and time duration reduction technique'... more We first show that for some kinds of signals a ''bandwidth and time duration reduction technique'' can be used to simulate waveform distortions caused by moving targets, that is, it is correct to measure the waveform distortions at very large TB with relatively small by reducing TB and increasing while keeping TB unchanged, where T is the duration of the transmitted signal, B is the bandwidth and is the relative speed of targets. We then study the waveform distortions in SAR signals caused by moving antenna. Based on the bandwidth and time duration reduction technique, a lot of time and memory are saved in simulations. We then confirm by simulations that waveform distortions do pose problems when processing very large bandwidth and long duration SAR data using conventional SAR processing methods. Finally we propose the concepts of wideband and narrowband processing of SAR data. Models are set up for wideband and narrowband SAR data processing, and new methods are presented for reconstructing targets using the proposed models. Simulations show that the methods can improve the quality of the simulated SAR images.
2010 IEEE International Conference on Communication Systems, 2010
We consider a distributed opportunistic spectrum access (D-OSA) scenario in which multiple cognit... more We consider a distributed opportunistic spectrum access (D-OSA) scenario in which multiple cognitive radio (CR) users attempt to access a channel licensed to some primary network. CR users operate on a frame-by-frame basis and need to carry out spectrum sensing at the beginning of each frame to determine whether the primary network is active or idle. Upon detecting the primary
IEEE Transactions on Wireless Communications, 2013
We survey the performance analysis of the suboptimal detectors in terms of probabilities of detec... more We survey the performance analysis of the suboptimal detectors in terms of probabilities of detection and false alarm, and selection of detection threshold and number of samples. With the prior knowledge that the primary user is highly likely idle and the primary signals are digitally modulated, Here a Bayesian detector (BD) for digitally modulated primary signals to maximize the spectrum utilization, without the prior information on the transmitted sequence of the primary signals is proposed. The proposed method makes use of the prior statistics of PU activity and the signalling information of the PU such as symbol rate and modulation order to improve the SU throughput and the overall spectrum utilization of both PUs and SUs.
IEEE Transactions on Wireless Communications, 2008
In a cognitive radio network, the secondary users are allowed to utilize the frequency bands of p... more In a cognitive radio network, the secondary users are allowed to utilize the frequency bands of primary users when these bands are not currently being used. To support this spectrum reuse functionality, the secondary users are required to sense the radio frequency environment, and once the primary users are found to be active, the secondary users are required to vacate the channel within a certain amount of time. Therefore, spectrum sensing is of significant importance in cognitive radio networks. There are two parameters associated with spectrum sensing: probability of detection and probability of false alarm. The higher the probability of detection, the better the primary users are protected. However, from the secondary users' perspective, the lower the probability of false alarm, the more chances the channel can be reused when it is available, thus the higher the achievable throughput for the secondary network. In this paper, we study the problem of designing the sensing duration to maximize the achievable throughput for the secondary network under the constraint that the primary users are sufficiently protected. We formulate the sensing-throughput tradeoff problem mathematically, and use energy detection sensing scheme to prove that the formulated problem indeed has one optimal sensing time which yields the highest throughput for the secondary network. Cooperative sensing using multiple mini-slots or multiple secondary users are also studied using the methodology proposed in this paper. Computer simulations have shown that for a 6MHz channel, when the frame duration is 100ms, and the signal-tonoise ratio of primary user at the secondary receiver is −20dB, the optimal sensing time achieving the highest throughput while maintaining 90% detection probability is 14.2ms. This optimal sensing time decreases when distributed spectrum sensing is applied.
Spectrum sensing, i.e., detecting the presence of primary users in a licensed spectrum, is a fund... more Spectrum sensing, i.e., detecting the presence of primary users in a licensed spectrum, is a fundamental problem in cognitive radio. Since the statistical covariances of received signal and noise are usually different, they can be used to differentiate the case where the primary user's signal is present from the case where there is only noise. In this paper, spectrum sensing algorithms are proposed based on the sample covariance matrix calculated from a limited number of received signal samples. Two test statistics are then extracted from the sample covariance matrix. A decision on the signal presence is made by comparing the two test statistics. Theoretical analysis for the proposed algorithms is given. Detection probability and associated threshold are found based on statistical theory. The methods do not need any information of the signal, the channel and noise power a priori. Also, no synchronization is needed. Simulations based on narrowband signals, captured digital television (DTV) signals and multiple antenna signals are presented to verify the methods.
Spectrum sensing is a fundamental component is a cognitive radio. In this paper, we propose new s... more Spectrum sensing is a fundamental component is a cognitive radio. In this paper, we propose new sensing methods based on the eigenvalues of the covariance matrix of signals received at the secondary users. In particular, two sensing algorithms are suggested, one is based on the ratio of the maximum eigenvalue to minimum eigenvalue; the other is based on the ratio of the average eigenvalue to minimum eigenvalue. Using some latest random matrix theories (RMT), we quantify the distributions of these ratios and derive the probabilities of false alarm and probabilities of detection for the proposed algorithms. We also find the thresholds of the methods for a given probability of false alarm. The proposed methods overcome the noise uncertainty problem, and can even perform better than the ideal energy detection when the signals to be detected are highly correlated. The methods can be used for various signal detection applications without requiring the knowledge of signal, channel and noise power. Simulations based on randomly generated signals, wireless microphone signals and captured ATSC DTV signals are presented to verify the effectiveness of the proposed methods.
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Papers by Yonghong Zeng