Spectrum sensing for the use of TV spectrum in North America is addressed in this paper. A unified signature-based spectrum sensing algorithm is designed for the primary licensed signals including NTSC analog TV and ATSC digital TV signals. In addition, an autocorrelation-based spectrum sensing algorithm is proposed for the secondary licensed signals such as wireless microphone signals. To our knowledge, the spectrum sensing algorithms presented in this paper are the first one which can reliably determine the availability of a TV channel for unlicensed radio transmissions in the presence of a strong adjacent channel interferer and the target signal strength is as low as -114 dBm.

OFDM spectrum sensing algorithms are presented in this paper. The proposed spectrum sensing algorithms are based on Time-Domain Symbol Cross-Correlation (TDSC-MRC and TDSC-NP methods) and can be applied to all existing wireless OFDM systems. The statistical behaviors of the TDSCbased spectrum sensors are explicitly analyzed. The sensing performances of the TDSC-based spectrum sensors in terms of misdetection probability are derived in detail. In addition, the spectrum sensing method employing the Cyclic Prefix of the OFDM modulated signals (CP method) is described for comparison purposes. The DVB-T Standard [5] is adopted as an application example to illustrate the proposed spectrum sensing algorithms. Simulation results show that the TDSC-MRC method outperforms the CP method for all values of CP ratio considered. The TDSC methods have the advantage that the detection performances are the same for different CP ratios, while the detection performance of the CP method degrades dramatically when the CP ratio becomes small. From simulation results, for a sensing time of 50 ms, the TDSC-MRC method can achieve misdetection probabilities of 0.1 and 0.01 with respect to a false alarm probability of 0.01 for SNR values of -20.5 dB and -19.5 dB, respectively.

Spectrum sensing is one of the core technologies of cognitive radio (CR) systems which provide a viable solution to the problem of sparsity of wireless spectrum. Nowadays, OFDM techniques are adopted by many existing or progressing wireless communication standards. Thus, a robust spectrum sensing algorithm for OFDM modulated signals is highly desired to implement CR when the primary signal uses OFDM modulation. Motivated by this demand, a time-domain symbol cross-correlation based spectrum sensing algorithm (TDSC method) is presented in this paper. The algorithm makes use of the property that the mean of the TDSC of two OFDM symbols is not zero if they have embedded the same frequency-domain pilot tones. The statistical behavior of the proposed spectrum sensor is explicitly analyzed and a theoretical lower bound on the misdetection probability is derived in this paper. An intuitive spectrum sensing method which utilizes the cyclic prefix nature of the OFDM modulated signals (CP method) is also described in this paper as a reference for comparison. Finally, we use the DVB-T Standard [8] as an application example to illustrate the proposed spectrum sensing algorithm. The simulated channel environments are the Ricean and Rayleigh channels defined in the DVB-T Standard and the additive white Gaussian noise (AWGN) channel. Four CP ratios defined in the DVB-T Standard are simulated for the probability of false alarm equaling 0.01 and the sensing time set equal to 50 ms. Simulation results show that the TDSC method can achieve a misdetection probability of 0.1 when the SNR equals -20.5 dB for all four CP ratios. The TDSC method outperforms the CP method in all cases. Furthermore, the proposed method has approximately the same detection performance for different CP ratios while the detection performance of the CP method degrades dramatically when the CP ratio becomes small. Results also reveal that the simulated performance is very close to the theoretical lower bound indicating that the lower bound can be used as a good prediction of performance.

Spectrum sensing for the China digital television terrestrial broadcasting system is considered in this paper. The spectrum sensing algorithms utilize PN sequences embedded in the frame headers to perform spectrum sensing. A theoretical lower bound on the misdetection probability for each spectrum sensor presented in this paper is derived. The performances of the proposed spectrum sensing algorithms are demonstrated by computer simulation for the multipath Rayleigh fading and steady state multipath Rayleigh fading channels. Simulation results show that the misdetection probability evaluated by computer simulations is close to the lower bound on the misdetection probability for a steady state multipath Rayleigh channel. When the probability of false alarm is 0.01 and a 50 ms of sensing time is used, a misdetection probability equal to 0.1 is achieved when the signal to noise power ratio is -16 dB, -18.8 dB, and -18 dB for modes 1, 2, and 3 in the multipath Rayleigh fading channel, respectively.

Spectrum sensing in a very low SNR environment (less than -20 dB) is considered in this paper. We make use of the noise rejection property of the cyclostationary spectrum. The sensing algorithms are based on measurement of the cyclic spectrum of the received signals. The statistics of the cyclic spectrum of the stationary white Gaussian process are fully analyzed for three measurement methods of the cyclic spectrum. The application to IEEE 802.22 WRAN is presented and the probability of false alarm is analytically derived. The operating characteristic curves for the sensing algorithms are determined from computer simulations using ATSC A/74 DTV signal captures as a test database.

Spectral sensing for the presence of ATSC DTV signals in VHF/UHF TV bands under a very low SNR environment is one of the core technologies in IEEE 802.22 WRAN. There are multiple signatures embedded in the ATSC DTV signals and these signatures can be utilized to perform spectrum sensing. Signature-based spectrum sensing algorithms have an advantage in that when the signals other than noise are detected, we are almost sure that they are signals we want to detect. Thus, in this paper, several signature based spectrum sensing algorithms are presented. The false alarm rate for detectors employing different algorithms is analytically derived. The operating characteristic curves for different detectors are determined from computer simulations using ATSC A/74 DTV signal captures as a test database.

The theory developed on the sequence optimization for equal-power code-division multiple-access (CDMA) systems is generalized in this paper. Unlike previous works, where discrete-time or vector channel models are predominantly employed, the overloaded channels are modeled as strictly band-limited, continuous-time multiple-access channels corrupted by additive white Gaussian noise (AWGN). After being posed as a multiple-input/single-output (MISO) joint transmitter and receiver optimization problem with the total mean-squared error (MSE) as the objective functional to be minimized, the variational problem is solved by using a frequency-domain approach. It is shown that there exist continuous-time equivalents of Welch bound equality (CTE-WBE) sequences as the jointly optimum transmit waveforms and that the matched filters are the jointly optimum receivers. The user capacity of the band-limited channels is characterized by a necessary and sufficient condition for the admissibility of users into the system in terms of the channel load, the received signal-to-noise ratio, and the signal-to-interference-plus-noise ratio (SINR) requirement. It is also shown that CTE-WBE sequences achieve the lower bound on the continuous-time equivalent of total squared correlation (CTE-TSC).

In this paper, the optimal signaling problem for multiple-access communications over Gaussian overloaded channels is considered with equal-power users having linear minimum mean-squared error (LMMSE) receivers. Unlike previous similar work on the sequence design for code-division multiple-access (CDMA) communications where discrete-time or vector channel models are predominantly employed, the overloaded channel is modeled as a strictly band-limited, continuous-time multiple-access channel corrupted by an additive white Gaussian noise. After being posed as a multi-input/single-output (MISO) joint transmitter and receiver optimization problem with the total mean-squared error as the objective functional, the variational problem is solved by using a frequency-domain approach. It is shown that the matched filters are the optimal receivers and that there exist continuous-time equivalents of Welch bound equality (CTE-WBE) sequences as the optimal transmit waveforms. The user capacity of the band-limited channel in terms of the admissibility of users into the system is also characterized by a necessary and sufficient condition on the channel load, the received signal-to-noise ratio, and the maximum signal-to-interference ratio.

Diversity combining of multiple time varying and correlated fading branches is investigated for direct-sequence spread-spectrum systems. The correlated branches are modeled and estimated jointly as a vector autoregressive (VAR) process. The joint estimation is shown to provide performance gain over separate estimation of the fading branches. The parameter matrices of the VAR model are estimated via the method of expectation maximization (EM) with two algorithms. The first algorithm, using results from Kalman smoothing, provides a closed-form solution to the maximization problem in the iterative EM procedure. However, the iterative EM-Kalman algorithm operates repeatedly on a batch of training data and results in large storage requirements and long processing delays. To overcome these disadvantages, a new algorithm with only forward-time recursions is proposed that approximates the iterative EM solution and efficiently adapts to slowly changing Doppler spreads. As a result, the new algorithm significantly reduces memory and training sequence requirements. Through computer simulations, a near ideal bit-error rate performance is found for both algorithms, and the efficacy of the new adaptive algorithm for channels with changing Doppler spreads is demonstrated.

The dependence of the error performance and spectral efficiency of direct-sequence spread-spectrum multiple-access (DS/SSMA) systems with matched filter receivers on the chip waveform is examined. The actual shape of the chip waveform, as well as its energy, is found to influence the statistical properties of the multiple-access interference (MAI). An approach to design waveforms that may result in interchip interference (ICI) is proposed and a criterion for design based on the conditional Gaussian approximation of the MAI for systems with aperiodic random spreading sequences is derived. For a simplified system, a closed-form solution for optimal band-limited waveforms is obtained for excess bandwidth less than or equal to one by using a performance metric that includes the effect of ICI. Numerical results, based on an analytical method, as well as Monte Carlo simulations, are provided to evaluate the performance of the proposed waveforms in general systems with conventional matched filter receivers.

In this paper, we consider the problem of fitting two users into a channel normally occupied by one user. The users share the same physical channel, but crosstalk is controlled. A linear receiver, which maximizes the signal-to-noise ratio (SNR) is employed, and several well known time-limited symbol waveforms are tested. Performance analysis shows that two users can be easily accommodated in a single-user channel with slight degradation of bit error rate (BER), and furthermore, near single-user performance is achievable by properly selecting the symbol waveform. A simple LMS-type algorithm is also discussed for adaptive implementation.

Cryo electron microscopy of viruses provides 2D projections of the scattering intensity of the viral particle but the orientation of the projections is not known. We describe an approach to reconstructing the 3D scattering intensity in spite of the unknown projection orientations using nonlinear least squares ideas where the reconstruction is guaranteed to have the icosahedral symmetry known to be present in the viral particle.