This paper deals with the capability of the orthogonal chirp division multiplexing (OCDM) modulation scheme to cope with multi-numerology concept in the context of next generations of communications. The OCDM-based multi-numerology transceiver is introduced, and the inter-numerology interference (INI) is analytically derived. The case of filtered-OCDM is considered as well, allowing to both reduce the INI and to shape the power spectrum of the composite signal (i.e. the signal composed of unitary signals configured with different numerologies) according to strong constraints of low out-of-band emissions. The simulations results show the inherent robustness of OCDM against INI as the interference is spread over all subcarriers, whereas it is concentrated in particular subcarriers in OFDM. It results that the (filtered)-OCDM waveform largely outperforms the orthogonal frequency division multiplexing (OFDM) in term of bit error rate (BER) performance, without need for a guard-band between numerologies.

This paper deals with peak to average power (PAPR) reduction in a single and multi-user orthogonal chirp division multiplexing (OCDM) context. Two methods for PAPR reduction based on the selection of the frequency variation (up or down) of the chirps are first presented in a single user system. The first technique consists in considering two OCDM signals generated with up and down chirps, respectively, and selecting the one offering lowest PAPR. The second PAPR reduction method is based on usual clipping, and in that case the chirp selection aims to reduce the clipping noise. An adapted receiver is also presented, based on the maximum likelihood (ML) estimation of the frequency variation (up or down) of the chirp. Then, a general procedure for multi-user OCDM transmission is introduced, where a sub-band of the available bandwidth is dedicated to each user, whose frequency of the chirps varies within this sub-band. Next, the PAPR reduction techniques are generalized to this multi-user OCDM system. Moreover, a performance analysis of the first PAPR reduction method is developed, and supported by simulation results. It is also shown that the chirp selection reduces the clipping noise, and improves the bit error rate performance compared with clipping only.

This paper deals with the orthogonal chirp division multiplexing (OCDM) modulation, and its capability to generate inherited waveforms, such as the orthogonal frequency division multiplexing (OFDM) or precoded OFDM, covering a large number of use cases. To this end, we first prove that the OCDM signal can be generated by a transmission chain composed of a discrete Fourier transform (DFT) matrix, followed by a multiplication by a chirp, and then an inverse DFT (IDFT). Then, we show that the OCDM transmission chain can be split into 6 sub-blocks from which we can generate numerous inherited waveforms. Thus, the OCDM waveform is an interesting candidate for flexible communication systems such as multiple radio access technology (multi-RAT).

This paper deals with quantization and clipping methods for complex Gaussian-like signal such as multicarrier waveforms in an software define radio (SDR) context. The process involving the quantization of the real and imaginary parts of any signal independently is a basic of digital signal processing, therefore plenty of papers about these techniques are available in the literature. In this paper, we rather consider the quantization of Gaussian complex signals as a whole. To this end, we base our quantization and clipping methods on norms such as Euclidean or infinity norms, allowing the quantized signal to keep the complex argument of the clipped signal samples unchanged and to reduce the peak to average power ratio (PAPR). Furthermore, we derive the corresponding performance analysis in terms of error vector magnitude (EVM), bit error rate (BER), and complexity. We show that simulations match the theoretical results, and that the suggested quantization methods outperform the usual one and reduces the PAPR of the signal, to the cost of an increase of complexity. Furthermore, we discuss the extension of the principle to any norm, as well as practical signals taken from standards such as 5G for instance.

This paper deals with multipath channel estimation and equalization in LoRa. It is suggested to take advantage of the cyclic property of the symbols in the LoRa frame preamble to obtain an interference-free version of the symbols in the frequency domain. Then, estimation methods used in multicarrier systems can be applied, such as the least square (LS), and the minimum mean square error (MMSE) estimators. It is shown that the cyclic property in LoRa is inherently independent of the length of the channel, making these estimation techniques robust to any frequency-selective channel. In addition the frequency domain zero-forcing (ZF) equalizer is used, and an original phase equalizer is introduced, taking advantage of the constant modulus property of LoRa symbols in the frequency domain. The performance of the investigated estimators and equalizers is shown through simulations, and applications to the presented results are further discussed.

This paper deals with a method of demodulation for oversampled LoRa signal. The usual maximum likelihood (ML) based demodulation method for LoRa chirp spread spectrum (CSS) waveform is dedicated to signals sampled at Nyquist rate, whereas considering oversampled signals may improve the performance of the LoRa demodulation process. In this respect, when an oversampling rate (OSR) 2 is assumed, the method suggested in this paper consists in applying two demodulation processes to the even and odd samples of the oversampled LoRa signal, and then combining the results. This principle is then generalized to any OSR, and we show that the complexity of the method is low since it only involves discrete Fourier transforms (DFT). Moreover, a performance analysis in terms of symbol and bit error rate (SER and BER) is presented considering both additive white Gaussian noise (AWGN) and Rayleigh channel models. Simulations show the relevance of the method and the performance analysis as a gain of 3 dB is achieved by the demodulation at OSR 2 compared with OSR 1.

This paper deals with an improved demodulation technique for LoRa signal. The principle consists in detecting the possible errors of demodulation, by comparing the highest peak of the periodogram of the dechirped received signal weighted by a coefficient beta? smaller than one with the other peaks of the periodogram. If an error is detected, a second demodulation stage is processed at an oversampling rate (OSR) higher than the first demodulation stage. Otherwise, the result of the first demodulation is kept. A thorough performance analysis of the suggested technique, based on order statistics, is carried out, in terms of detection rate, error rate, and complexity. It is shown that beta? can be tuned to adjusts the trade-off between performance and complexity. Moreover, simulations results shows that it is possible, for relatively low signal-to-noise (SNR) values, to reach the performance of the demodulation at highest OSR while keeping the complexity of the demodulation at lowest OSR.

This paper deals with the bit error rate (BER) of LoRa signal over Rayleigh and Rice channels. Exact analytical expressions of the BER in LoRa systems have been proposed in the literature, but they are not tractable and raise problems of computation precision. We then hereby suggest asymptotic expressions of the BER, which are at the same time tractable and accurate over a wide BER range. source code: https://github.com/b-com/ber_LoRa

This paper deals with time and frequency synchronization in LoRa system based on the preamble symbols. A thorough analysis of the maximum likelihood (ML) estimator of the delay (time offset) and the frequency offset shows that the resulting cost function is not concave. As a consequence the a priori solution to the maximization problem consists in exhaustively searching over all the possible values of both the delay and the frequency offset. Furthermore, it is shown that these parameters are intertwined and therefore they must be jointly estimated, leading to an extremely complex solution. Alternatively, we show that it is possible to recover the concavity of the cost function, from which we suggest a low-complexity synchronization algorithm, whose steps are described in detail. Simulations results show that the suggested method reaches the same performance as the ML exhaustive search, while the complexity is drastically reduced, allowing for a real-time implementation of a LoRa receiver.

This paper deals with a cloud radio access network (CRAN) architecture for the LoRa system. In the suggested design, the gateway embeds a limited remote radio head (RRH), including the analog radio-frequency (RF) analog part, the digital-to-analog and analog-to-digital conversion, and a digital front-end (DFE). The other LoRa network functions, including the physical (PHY) layer, the LoRaWAN medium access control (MAC) layer, and the application and customer servers are implemented as cloud resources. The presented approach leads to a flexible RAN that is robust to the variations of capacity needs. Furthermore, it allows us to test very specific LoRa features, such as the detection or demodulation, while bypassing the other ones including the hardware RRH. The methodology and tools we used to deploy a LoRa cloud RAN are detailed, and results concerning the performance indicator (CPU load, memory consumption) are provided as well.

This paper proposes a flexible multi-standard digital frontend (DFE) hardware architecture designed for three main low-power wide-area (LPWA) technologies: LoRa, Sigfox, and narrowband-Internet of things (NB-IoT).We demonstrate the feasibility of an unified DFE architecture that fits the requirements of these LPWA technologies. The proposed DFE architecture has been implemented on a Spartan-6 field programmable gate array (FPGA) within a base station receiver, and tested using a universal software radio peripheral (USRP) based platform. We show that the expected performance can be achieved with low hardware complexity, in terms of memory and logic requirements.

This paper deals with cell ID estimation in narrowband-internet of things (NB-IoT) system. The cell ID value is carried by the narrowband secondary synchronization signal (NSSS). We suggest a low-complexity sub-optimal estimator, based on the auto- correlation of the received observations. It is up to thirty times less complex than the optimal maximum likelihood (ML) estimator based on cross-correlation. In addition, we present three methods allowing the receiver to take advantage of the different repetitions of the NSSS. They are based on a hard decision after every estimation, a soft combination of the different observations of the NSSS, and an hybrid mix between the two firsts, respectively. The advantages and drawbacks of the presented techniques are stated, and a performance analysis is proposed, which is further discussed through simulations results. It is shown the that different methods reach the performance of ML after several repetitions for a lower overall complexity.