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IEEE 802.15.4 is a popular standard for low-rate wireless communications used for the Internet of Things (IoT). This IEEE standard contains a variety of physical layers (such as SUN, TVWS, RCC LMR, and LECIM) that make use of different modulations, such as nonorthogonal frequency-shift keying (FSK) and position-based FSK. This paper proposes simple closed-form expressions to evaluate the bit-error rate (BER) performance of nonorthogonal FSK schemes used for the IoT. Both coherent and noncoherent detection cases are investigated in additive white Gaussian noise (AWGN) and frequency-nonselective fading channels. In case of AWGN channels, the proposed BER expressions are obtained by selecting and modifying two terms of a union bound on the error probability. In case of fading channels, the proposed BER expressions are obtained by integration of the conditional BER over the fading statistics. Simulation results confirm the good accuracy of the proposed analytical BER expressions for different channel models (such as AWGN, Nakagami-m, Rice, lognormal) and for different detection techniques (such as noncoherent, coherent, and coherent with a residual phase error). Experimental results with wireless transmission and reception confirm the accuracy of the proposed approach. In addition, this paper also presents a BER expression for coherent detection of position-based FSK. Simulation results demonstrate that the presented BER expression for position-based FSK is more accurate than the BER expressions proposed in the literature.

Due to the explosion in the demand for broadband wireless services by consumers, wireless network service providers require increased frequency allocations from an already crowded frequency spectrum. In an effort to satisfy the increased frequency spectrum requirements of wireless communications networks, several methods have been proposed to allow communication systems and radars to co-exist within the same bandwidth or adjacent frequency bands while minimizing or preventing mutual interference. Most methods explored in the literature focus on the use of cognitive sensing and dynamic spectrum allocation. Other proposed methods to prevent mutual interference between radar and communications systems focus on waveform design. In this manuscript, a dual function communication and radar system with EMCON applications is investigated that uses Gold or Kasami codes in a code shift keying digital modulation scheme. The use of both binary phase shift keying (BPSK) and quaternary phase shift keying (QPSK) to modulate the code bits is investigated. The communications signal is used as the radar signal to implement a pseudo-random BPSK or QPSK coded radar. The symbol error rate (SER) of the communication system is determined through Monte Carlo simulations and compared to an SER upper bound for M-ary frequency shift keying. The radar signal's periodic autocorrelation function (PACF) and periodic ambiguity function are also examined demonstrating the schemes potential for use in a low probability of intercept radar application. The radar signal's characteristics are compared when using pseudo-random BPSK and QPSK modulations.

This paper presents a novel digital data modulation and demodulation algorithm ARDMA based on the principles of autoregressive modeling (AR) of speech production. In the first step a sustained voiced speech signal characteristics are analyzed using autoregressive modeling principle and then the two sets of linear prediction (LPC) coefficients are obtained and converted to linear spectrum frequencies (LSF). The input binary data stream drives the selection mechanism of LSF coefficients which are then applied as filter coefficients of the modulation signal synthesis filter. This filter is excited with specially designed excitation signal which corresponds to the basic characteristics of typical excitation signal of human vocal tract. Finally, a speech-alike modulation signal is produced. This modulation signal is then sent through the voice channel of the GSM system. The demodulator analyzes the incoming modulation signal using autoregressive modeling. The most likely LSF vector which modulated the particular symbol was determined by the demodulation process and converted to the respective string of binary data. The performance of proposed modulation scheme was compared to the regular frequency shift keying method (FSK). The performance improvement of ARDMA against FSK is observed at higher bit-rates in the case of three compared GSM speech coders.