LoRa Backscatter Communications: Temporal, Spectral, and Error Performance Analysis

LoRa backscatter (LB) communication systems can be considered as a potential candidate for ultra low power wide area networks (LPWAN) because of their low cost and low power consumption. In this paper, we comprehensively analyze LB modulation from various aspects, i.e., temporal, spectral, and error performance characteristics. First, we propose a signal model for LB signals that accounts for the limited number of loads in the tag. Then, we investigate the spectral properties of LB signals, obtaining a closed-form expression for the power spectrum. Finally, we derived the symbol error rate (SER) of LB with two decoders, i.e., the maximum likelihood (ML) and fast Fourier transform (FFT) decoders, in both additive white Gaussian noise (AWGN) and double Nakagami-m fading channels. The spectral analysis shows that out-of-band emissions for LB satisfy the European Telecommunications Standards Institute (ETSI) regulation only when considering a relatively large number of loads. For the error performance, unlike conventional LoRa, the FFT decoder is not optimal. Nevertheless, the ML decoder can achieve a performance similar to conventional LoRa with a moderate number of loads.Comment: Early access in IEEE Journal of Internet of Things. Codes are provided in Github: https://github.com/SlinGovie/LoRa-Backscatter-Performance-Analysi

Bit error rate closed-form expressions for lora systems under nakagami and rice fading channels

We derive exact closed-form expressions for Long Range (LoRa) bit error probability and diversity order for channels subject to Nakagami-m, Rayleigh and Rician fading. Analytical expressions are compared with numerical results, showing the accuracy of our proposed exact expressions. In the limiting case of the Nakagami and Rice parameters, our bit error probability expressions specialize into the non-fading case1920CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQ313239/2017-7; 304946/2016-

Coded LoRa Frame Error Rate Analysis

In this work, we study the coded frame error rate (FER) of LoRa under additive white Gaussian noise (AWGN) and under carrier frequency offset (CFO). To this end, we use existing approximations for the bit error rate (BER) of the LoRa modulation under AWGN and we present a FER analysis that includes the channel coding, interleaving, and Gray mapping of the LoRa physical layer. We also derive the LoRa BER under carrier frequency offset and we present a corresponding FER analysis. We compare the derived frame error rate expressions to Monte Carlo simulations to verify their accuracy

Golden Modulation: a New and Effective Waveform for Massive IoT

This paper considers massive Internet of Things systems, especially for LoW Power Wide Area Networks, that aim at connecting billions of low-cost devices with multi-year battery life requirements. Current systems for massive Internet of Things exhibit severe problems when trying to pursue the target of serving a very large number of users. In this paper, a novel asynchronous spread spectrum modulation, called Golden Modulation, is introduced. This modulation provides a vast family of equivalent waveforms with very low cross-interference even in asynchronous conditions, hence enabling natural multiuser operation without the need for inter-user synchronization or for interference cancellation receivers. Thanks to minimal interference between waveforms, coupled with the absence of coordination requirements, this modulation can accommodate very high system capacity. The basic modulation principles, relying on spectrum spreading via direct Zadoff-Chu sequences modulation, are presented and the corresponding theoretical bit error rate performance in an additive white Gaussian noise channel is derived and compared by simulation with realistic Golden Modulation receiver performance. The demodulation of the Golden Modulation is also described, and its performance in the presence of uncoordinated multiple users is characterized.Comment: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl