Minimum shift keying

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The authors present theoretical performance analysis and simulation results for Quadrature-Quadrature Phase Shift Keying (Q2 PSK), Constant Envelope (CE) Q2 PSK, and trellis coded 16D CEQ2 PSK in ideal bandlimited channels of various bandwidths. The performance of receivers with and without channel estimation is reported. Spectral analysis is presented for each system, in addition to MSK and expanded uncoded 16D CEQ2 PSK. We show that the effects of bandlimiting are most severe for Q2 PSK. Knowledge of the channel information aids 4D CEQ2 PSK the least. Only 6.8 dB of SNR is needed for the TCM system for a bit error rate of 10-5 for the narrowest channel bandwidth studied here, if the receiver has knowledge of the channel.

The past researches shows GMSK (Gaussian minimum shift keying) & OFDM (Orthogonal frequency division multiplexing) are the most effective techniques in the area of wireless communication. There have been many platforms to analyze the working and performance of GMSK & OFDM. In this paper, the experiment is performed on the SDR (software defined radio) which is more flexible radio system as compared to the other conventional radios. A flexible open source system GNU Radio is used to limelight the importance of GMSK communication. This paper focuses on the implementation of GMSK modulator & demodulator and analyzes the working & results of a video communication using GMSK modulation technique. The real time video signal transmission and reception is performed using USRP (Universal software radio peripheral) and configured by GNU Radio 3.7.5.1 in the laboratory environment.

Satellite transmissions classically use constant amplitude linear modulation schemes, such as M-state phase shift keying (M-PSK), because of their high robustness to amplifier non-linearities. However, other modulation formats are interesting in a satellite transmission context. For instance, non-linear modulations such as Gaussian minimum shift keying (GMSK) present a higher spectral efficiency and appear in new standards for telemetry/telecommand satellite links. Another example is offset-QPSK (OQPSK) modulation that allows one to decrease the out-of-band interference due to band limiting and the non-linearity of the amplifier. To get a compromise between the robustness to amplifier non-linearities provided by MPSK modulation and the spectral efficiency given by QAM modulation, the recent broadcasting satellite standard (DVB-S2) proposes new modulation schemes called APSK. Obviously, all satellite systems that use various modulation schemes will have to co-exist. In this context, modulation recognition using the received communication signal is essential. In that context, this paper studies two Bayesian classifiers to recognize linear and non-linear modulations. These classifiers estimate the posterior probabilities of the received signal, given each possible modulation, and plug them into the optimal Bayes decision rule. Two algorithms are used for that purpose. The first one generates samples distributed according to the posterior distributions of the possible modulations using Markov chain Monte Carlo (MCMC) methods. The second algorithm estimates the posterior distribution of the possible modulations using the Baum-Welch (BW) algorithm. The performance of the resulting classifiers is assessed through several simulation results.

Satellite transmissions classically use constant amplitude linear modulation schemes, such as M-state phase shift keying (M-PSK), because of their high robustness to amplifier non-linearities. However, other modulation formats are interesting in a satellite transmission context. For instance, non-linear modulations such as Gaussian minimum shift keying (GMSK) present a higher spectral efficiency and appear in new standards for telemetry/telecommand satellite links. Another example is offset-QPSK (OQPSK) modulation that allows one to decrease the out-of-band interference due to band limiting and the non-linearity of the amplifier. To get a compromise between the robustness to amplifier non-linearities provided by MPSK modulation and the spectral efficiency given by QAM modulation, the recent broadcasting satellite standard (DVB-S2) proposes new modulation schemes called APSK. Obviously, all satellite systems that use various modulation schemes will have to co-exist. In this context, modulation recognition using the received communication signal is essential. In that context, this paper studies two Bayesian classifiers to recognize linear and non-linear modulations. These classifiers estimate the posterior probabilities of the received signal, given each possible modulation, and plug them into the optimal Bayes decision rule. Two algorithms are used for that purpose. The first one generates samples distributed according to the posterior distributions of the possible modulations using Markov chain Monte Carlo (MCMC) methods. The second algorithm estimates the posterior distribution of the possible modulations using the Baum-Welch (BW) algorithm. The performance of the resulting classifiers is assessed through several simulation results.

The composite Rayleigh-lognormal distribution is mathematically intractable for the analytical evaluation of such a communication system performance metric as bit error rate. The composite K distribution closely approximates the Rayleigh-lognormal and is potentially useful for analytical manipulations. In this contribution we derive the bit error rates of DPSK and MSK, in manageable closed forms, for the K distribution model of multipath fading and shadow fading, and show, numerically, the close agreement between these results and those based on the Rayleigh-lognormal distribution.

In this paper, in order to compress and enhance 2D images transmitted over wireless channels, a new scheme called Kalman-Turbo (KT) is introduced. In this scheme, the original image is partitioned into 2 N quantization levels and each of the N-bit planes is coded by Turbo encoder. After noise corruption of the channel, each of the noisy bit planes is processed iteratively by a joint equalization block, which is composed of low-complexity 2D binary Kalman filter and the Turbo decoder. In our Kalman filter, state equations are modified in order to take the advantage of two-dimensionality, and, previous soft decisions are taken into account to avoid divergence of Kalman filter. Simulation results show that the performance of the KT system is superior at low SNRs when compared with that of plain Turbo decoding algorithms. We can also achieve compression by any selection of N. Hence, we conclude that KT system will be a compromising approach in 2D image transmission.

In this paper, we applied Continuous Phase Frequency Shift Keying (CPFSK) to Trellis Coded Quantization/Modulation (TCQ/TCM) and thus we called Trellis Coded Quantization/ Continuous Phase Modulation (TCQ/TCCPM) for this new sys- tem. In this new scheme we use continuous phase frequency shift keying signal set instead of phase shift keying signal set. As an example, an eight state TCQ/TCCPM system is designed and its error performance is evaluated for different Rician fading parameters K and signal to noise ratios.