In this paper, we propose a spectral-efficient LoRa (SE-LoRa) modulation scheme with a low complexity successive interference cancellation (SIC)-based detector. The proposed communication scheme significantly improves the spectral efficiency of LoRa modulation, while achieving an acceptable error performance compared to conventional LoRa modulation, especially in higher spreading factor (SF) settings. We derive the joint maximum likelihood (ML) detection rule for the SE-LoRa transmission scheme that turns out to be of high computational complexity. To overcome this issue, and by exploiting the frequency-domain characteristics of the dechirped SE-LoRa signal, we propose a low complexity SIC-based detector with a computation complexity at the order of conventional LoRa detection. By computer simulations, we show that the proposed SE-LoRa with low complexity SIC-based detector can improve the spectral efficiency of LoRa modulation up to 445.45%, 1011.11%, and 1071.88% for SF values of 7, 9, and 11, respectively, while maintaining the error performance within less than 3 dB of conventional LoRa at symbol error rate (SER) of 10−3in Rician channel conditions.

In this article, we propose a multiple-input-multiple-output (MIMO) configuration for chirp spread spectrum (CSS) modulation integrated with the permutation matrix modulation (PMM) scheme, namely, MIMO-CSS-PMM. The proposed MIMO-CSS-PMM simultaneously improves the spectral efficiency (SE) and error performance of the CSS-based transmission scheme. For the detection, we formulate the optimum maximum-likelihood (ML) detector that turns out to be of high computational complexity. We propose two low complexity semi-coherent detection schemes, i.e., scheme I and scheme II, in which we average over the fast Fourier transform (FFT) output of the dechirped signal of each receiver antenna. Then, in scheme I, we reduce the ML search set by selecting the number of largest averaged signal values corresponding to the number of transmitter antennas. To further reduce the complexity of scheme I, in scheme II, we define and derive a probability of detection using concepts from order statistics and find a threshold value maximizing this probability of detection. We select the number of the largest averaged signal greater than or equal to the obtained threshold to eliminate the unnecessary cases from the search set of scheme I. With the help of computer simulations, we evaluate the proposed detectors in terms of bit error rates (BERs).

In this paper, we investigate the coexistence between two of the most common long-range wide area network (LoRaWAN) transmission schemes, i.e., LoRa chirp and long-range frequency hopping spread spectrum (LR-FHSS). We consider a system model in which LoRa chirp and LR-FHSS modulations are deployed in two overlapping terrestrial and direct-to-satellite internet of things (DtS-IoT) networks, respectively. We derive the maximum likelihood (ML) detection rule for the joint detection of the LoRa chirp and the interfering portion of LR-FHSS fragments at the terrestrial LoRa gateway (GW). Due to the high complexity of the joint ML detector, and since our focus is primarily on the detection of the LoRa chirp at the LoRa GW, we propose a filtering-based detector for the LoRa chirp which benefits from the narrowband frequency characteristics of the LR-FHSS signal as the interference. Simulation results show that the error performance of the proposed filtering-based detection for the LoRa chirp degrades by 2 dB, 1 dB, and less than 0.5 dB for SF = 7, SF = 9, and SF = 11, respectively, at bit error rate (BER) of 10−4in additive white Gaussian noise (AWGN), compared to the case when the LR-FHSS interference does not exist. Moreover, for Rayleigh fading channel conditions, the proposed filtering-based detection scheme can achieve an acceptable performance in high values of signal-to-interference ratio (SIR).

Long-range frequency-hopping spread spectrum (LR-FHSS) is a new transmission protocol introduced under the long-range wide area network (LoRaWAN) specifications to tackle the issue of extremely long-range and large-scale internet of things (IoT) deployment scenarios. Unlike the other LoRaWanscheme, i.e., the one based on the chirp spread spectrum (CSS) modulation, the physical layer of LR-FHSS exploits a 488 Hz Gaussian minimum shift keying (GMSK) modulation. In this paper, we investigate and model the FHSS-GMSK modulation and evaluate its bit error rate (BER) performance in the LR-FHSS system using simulations. We also propose a low-complexity GMSK signal detection scheme that can be used at the gateway (GW) of an IoT network with a massive number of IoT end devices (EDs). Using computer simulations, we show that our proposed detector can offer a tradeoff between the complexity of the receiver and the bit error rate (BER) performance.

In this article, we present a device-to-device (D2D) transmission scheme for aiding long-range frequency-hopping spread spectrum (LR-FHSS) LoRaWAN protocol with application in direct-to-satellite Internet of Things (IoT) networks. We consider a practical ground-to-satellite fading model, i.e., shadowed-Rice channel, and derive the outage performance of the LR-FHSS network. With the help of network coding, a D2D-aided LR-FHSS transmission scheme is proposed to improve the network capacity for which a closed-form outage probability expression is also derived. The obtained analytical expressions for both LR-FHSS and D2D-aided LR-FHSS outage probabilities are validated by computer simulations for different parts of the analysis capturing the effects of noise, fading, unslotted ALOHA-based time scheduling, the receiver’s capture effect, IoT device distributions, and distance from node to satellite. The total outage probability for the D2D-aided LR-FHSS shows a considerable increase of 249.9% and 150.1% in network capacity at a typical outage of 10−2 for the data rates of DR6 (325 bps) and DR5 (162 bps), respectively, when compared to LR-FHSS. This is obtained at the cost of a minimum of one and a maximum of two additional transmissions per IoT end device imposed by the D2D scheme in each time slot.

Peak‐to‐average power ratio (PAPR) is the main parameter affecting the implementation cost of wireless transmitters utilising carrier aggregation in the end‐users' channels. In each frequency band, single‐carrier frequency division multiple access (SC‐FDMA) is exploited as the interface from the transmitter to the receiver, and carrier aggregation is implemented by SC‐FDMA on each band. Hence, the power amplifier simultaneously amplifies signals of multiple bands, meaning that its PAPR is affected by the use of multiple SC‐FDMA channels. In this study, a novel method has been proposed for the delay and PAPR reduction in carrier aggregation systems. Also, a novel recursive method is proposed to reduce the computational complexity of the proposed partial transmit sequence (PTS) algorithm. Utilising computer simulations, it has been shown that the PAPR can be reduced by 3.5 dB for the time‐domain PTS method in mapping for the three‐band SC‐FDMA comparing to existing methods.

In this study, a cognitive radio network is considered in which multiple secondary users intend to detect a primary user frequency band in order to specify whether it is occupied or not. To this end, a blind Bayesian framework is proposed by which secondary users cooperatively perform spectrum sensing. In practice, it is impossible to estimate the noise variance accurately (noise uncertainty problem) and this can degrade the performance of some previous spectrum sensing algorithms like energy detection (ER). To overcome this issue, unlike the conventional ER, the proposed algorithm utilises marginalisation to eliminate the effect of uncertainty in noise variance estimation. By computer simulations using MATLAB, it can be seen that the authors' algorithm reaches the ideal case for by improving the level of cooperation (increasing the number of secondary users) and yet its is also improved compared to ER in practical situations (presence of noise uncertainty).