Modulation Identification and Carrier Recovery System for Adaptive Modulation in Satellite Communications

We introduce the modulation identification technique implementing the multimode phase locked loop (PLL) in the satellite communication using adaptive modulation scheme which is a countermeasure against the rain attenuation. In the multimode PLL, phase lock detectors (PLDs) are used for not only phase lock, but also modulation identification. We present the sub-optimized design of the PLDs for modulation identification with respect to the throughput and show the validity of sub-optimization. In addition, by the comparison between the multimode PLL and conventional scheme in ISDB-S, we present the effectivity of the multimode PLL

Method of Non-Data-Aided Carrier Recovery with Modulation Identification

A non-data aided carrier recovery technique using digital modulation format identification called multi-mode PLL (Phase Locked Loop) is proposed. This technique can be interpreted as a modulation identification method that is robust against static phase and frequency offsets. The performance of the proposed technique is studied and the analytical expressions are derived for the probability of lock detection, acquisition time over AWGN channel in the cases of M-PSK and M-QAM modulations with respect to frequency offset and signal-to-noise ratio

A Method of Non-Data-Aided Carrier Recovery with Modulation Identification

A non-data aided carrier recovery technique using modulation format identification is proposed. This technique can also be interpreted as a modulation identification method that is robust against static phase and frequency offsets. The performance of the proposed technique is studied and analytical expressions derived for the mean acquisition time to detect lock in the cases of M-PSK, M=2,4,8, and 16-QAM modulation, with respect to frequency offset and signal-to-noise ratio. The results are verified with Monte Carlo simulations. The main advantage of the proposed method lies in its simpler implementation and faster lock detection, when compared to conventional methods

Improved channel occupancy rate estimation

Channel occupancy rate (COR) is the fraction of the time that a channel is occupied, i.e., contains signal(s) in addition to noise. Estimation of COR is important, e.g., in cognitive radio systems, which can use this information for intelligently adapting their spectrum use to the operating environment. For COR estimation, both the ability to operate with weak signals (sensitivity) and closeness of the estimate to the true COR value (accuracy) are important. In this paper, an improved COR estimation (iCOR) method is proposed enabling the use of high false alarm probabilities to improve sensitivity without the overestimation usually associated with high false alarm probabilities. The iCOR method is compared with the conventional method in terms of worst-case root-mean-square error (RMSE), which refers to the RMSE for the COR level yielding the maximum RMSE. To fairly compare different COR estimation methods, it is required that the RMSE for strong signals equals a target value and the considered methods are compared by their RMSE for weaker signals. Comprehensive theoretical analysis is performed and both exact results and approximations are derived. Experimental results verify the theoretical analysis and show significant sensitivity gains from the iCOR method (around 5 dB)

A Study on High-Efficiency Energy Detection-Based Spectrum Measurements

Statistical information in terms of spectrum occupancy is useful for the efficient and smart dynamic spectrum sharing, and it can be obtained by long-term, broadband, and wide-area spectrum measurements. In this paper, we investigate an energy detection (ED)-based spectrum measurements, in which the noise floor (NF) estimation is a key functionality for the appropriate ED threshold setting. Typically, the NF has the slowly time- varying property and frequency-dependency, and several NF estimation algorithms, including forward consecutive mean excision (FCME) algorithm-based method, have been proposed. However, these methods did not deeply consider the slowly time varying property of the NF and is computationally inefficient. Accordingly, we propose a computational complexity reduction algorithm based on NF level change detection. This algorithm is computationally efficient, since it skips the NF estimation process when the NF does not change. In numerical evaluations, we show the efficiency and the validity of the proposed algorithm