In modern communication systems, it is a critical and challenging issue for existing carrier tracking techniques to achieve near-ideal carrier synchronization without the help of pilot signals in the case of symbol rate sampling and low signal-to-noise ratio (SNR). To overcome this issue, this paper proposes an effective carrier frequency and phase offset tracking scheme which has a robust confluent synchronization architecture whose main components are a digital frequency-locked loop (FLL), a digital phase-locked loop (PLL), a modified symbol hard decision block and some sampling rate conversion blocks. As received signals are sampled at symbol baud rate, this carrier tracking scheme is still able to obtain precise estimated values of carrier synchronization parameters under the condition of very low SNRs. The performance of the proposed carrier synchronization scheme is also evaluated by using Monte-Carlo method. Simulation results confirm the feasibility of this carrier tracking scheme and demonstrate that it ensures that both the rate-3/4 irregular low-density parity-code (LDPC) coded system and the military voice transmission system utilizing the direct sequence spread spectrum (DSSS) technique achieve satisfactory bit-error rate (BER) performance at correspondingly low SNRs.

Automatic modulation classification (AMC) is an important function of radio surveillance systems in order to identify unknown signals. Many previous works on AMC have utilized signal cyclostationarity, particularly spectral correlation density (SCD), but many of them fail to address several implementation issues, such as the assumption of perfect knowledge of the symbol rate. In this paper, we discuss several practical issues, e.g. cyclic frequency mismatch, which may affect the SCD, and propose compensation techniques to overcome those issues. We also propose a novel feature extraction technique from the SCD, which utilizes the SCD of not only the original received signal, but also the squared received signal. A symbol rate estimation technique which complements the feature extraction is also proposed. Finally, the classification performance of the system is evaluated through Monte Carlo simulations using a wide variety of modulated signals, and simulation results show that the proposed technique can estimate the symbol rate and classify modulation with a probability of above 0.9 down to SNRs of 5 dB.

Automatic modulation classification (AMC) involves extracting a set of unique features from the received signal. Accuracy and uniqueness of the features along with the appropriate classification algorithm determine the overall performance of AMC systems. Accuracy of any modulation feature is usually limited by the blindness of the signal information such as carrier frequency, symbol rate etc. Most papers do not sufficiently consider these impairments and so do not directly target practical applications. The AMC system proposed herein is trained with probable input signals, and the appropriate decision tree should be chosen to achieve robust classification. Six unique features are used to classify eight analog and digital modulation schemes which are widely used by low frequency mobile emergency radios around the globe. The Proposed algorithm improves the classification performance of AMC especially for the low SNR regime.

A new seamless symbol rate switchable modem for multi-rate FDMA systems is proposed in this paper. In the new modem, a novel clock phase compensation algorithm makes it possible to switch the symbol rate synchronously between the transmitter and the receiver, with no degradation in BER when the symbol rate is changed. In addition, by matching the interpolation filter to the symbol rate, this modem is capable of operating at lower clock speeds, which greatly reduces the consumption power. Computer simulations confirm its fundamental performance. Simulation results show that the proposed power-efficient symbol rate switchable modem can change the symbol rate without degrading BER performance.

The cyclic autocorrelation of common digital modulation is researched, and the relationship between the cyclic autocorrelation and the delay, corresponding to the symbol rate, is deduced, then a searching algorithm for the symbol rate is proposed. Theoretical analyses and simulation results show that this method has less computation complexity and is also quite accurate. The estimation result is almost immune to the stationary noise. It's of practical value to modulation recognition and blind demodulation.

Quasi-millimeter-wave-band Fixed Wireless Access (FWA) systems have higher transmission rates than 2.4-GHz or 5-GHz systems, because the available frequency bandwidth for quasi-millimeter-wave-bands is broader than the 2.4-GHz and 5-GHz bands. However, quasi-millimeter-wave-band systems are unsuitable for long-span transmission because the attenuation caused by rain is large. We propose that the symbol rate be lowered for rainfall; i.e., when it rains, a low symbol rate is used. This means narrowing the equivalent noise bandwidth so that a margin for rain attenuation is obtained. We compared a method in which the symbol rate is either high or low with one in which the symbol rate is selectable over a range of values. We verified the beneficial effect of the two-rate method through calculations and simulations. A case study in the Tokyo metropolitan area showed that the service zone radius of this method is double that of conventional systems. Changing to a low symbol rate decreases the transmission rate, but periods of heavy rainfall comprise only about 1% of the amount of time in a year, and so the average decrease in the transmission rate is approximately zero.