According to the recent 3GPP decisions on 6G air interface, orthogonal frequency-division multiplexing (OFDM)-based waveforms are the primary candidates for future integrated sensing and communication (ISAC) systems. In this paper, we consider a monostatic sensing scenario in which OFDM is used for the downlink and its reflected echo signal is used for sensing. OFDM and discrete Fourier transform-spread OFDM (DFT-s-OFDM) are the options for uplink transmission. When OFDM is used in the uplink, the power difference between this signal and the echo signal leads to a power-domain non-orthogonal multiple access (PD-NOMA) scenario. In contrast, adopting DFT-s-OFDM as uplink signal enables a waveform-domain NOMA(WD-NOMA). Affine frequency-division multiplexing (AFDM) and orthogonal time frequency space (OTFS) have been proven to be DFT-s-OFDM based waveforms. This work focuses on such a WD-NOMA system, where AFDM or OTFS is used as uplink waveform and OFDM is employed for downlink transmission and sensing. We show that the OFDM signal exhibits additive white Gaussian noise (AWGN)-like behavior in the affine domain, allowing it to be modeled as white noise in uplink symbol detection. To enable accurate data detection performance, an AFDM frame design and a noise power estimation (NPE) method are developed. Furthermore, a two-dimensional orthogonal matching pursuit (2D-OMP) algorithm is applied for sensing by iteratively identifying delay-Doppler components of each target. Simulation results demonstrate that the WD-NOMA ISAC system, employing either AFDM or OTFS, outperforms the PD-NOMA ISAC system that uses only the OFDM waveform in terms of bit error rate (BER) performance. Furthermore, the proposed NPE method yields additional improvements in BER.

Integrated sensing and communication (ISAC) in monostatic in-band full-duplex (IBFD) systems encounters significant challenges due to self-interference (SI) at the radar receiver during concurrent communication and radar operations. This paper proposes a novel waveform-domain self-interference cancellation (SIC) technique that leverages the unique properties of orthogonal frequency division multiplexing (OFDM) and affine frequency division multiplexing (AFDM) signals. The proposed approach designs the integrated dual-functionality frame to utilize OFDM for communication and AFDM for radar sensing, both generated using the same modulator block. Then, we establish the conditions under which a wide sense stationary (WSS) process in the time domain appears as WSS in the affine domain and demonstrate that the interfering OFDM signal behaves as an additive white Gaussian noise (AWGN) in this domain. Exploiting this property, the received signal is projected into the affine domain, where the SI appears as AWGN, enabling its subtraction with minimal residual interference. To further mitigate the residual SI, an iterative low-complexity windowing scheme is applied, selectively locking onto the radar signal to reduce the processed signal space. A subsequent time domain spreading step is applied after converting the SIC-processed signal into the post-coded time domain, wherein the SI diminishes separately across the delay and Doppler axes. The proposed method demonstrates superior performance in terms of detection probability, target’s range and velocity root mean square error (RMSE), while maintaining high spectral efficiency and minimal computational complexity.

Long-Range (LoRa) technology holds tremendous potential for regulating and coordinating communication among Internet-of-Things (IoT) devices due to its low power consumption and cost-effectiveness. However, LoRa faces significant obstacles such as reduction in coverage area, a high packet drop ratio (PDR), and an increased likelihood of collisions, all of which result in substandard data rates. In this paper, we present a novel approach that employs a relaying node capable of allocating resources dynamically based on signal parameters. In particular, the geometric placement of the relay node is determined by a genetic algorithm that maximizes signal-to-noise ratio (SNR) and signal-to-interference ratio (SIR) success probabilities. Using equal-area based (EAB) spreading factor (SF) distance allocation scheme, the coverage area is sliced into distinct regions in order to derive the success probabilities for different communication stages. Furthermore, we present a frequency channel shuffling algorithm to prevent collisions between end devices (EDs) without increasing the complexity of the relaying nodes. Through extensive simulations, we demonstrate that our proposed scheme effectively expands the coverage area, conserves transmission resources, and enhances the system’s throughput. Specifically, our approach extends the range by up to 40%, increases the throughput by up to 50% compared to conventional methods, and achieves a 40% increase in success probability. To validate the practicality of our approach, we implement our algorithm in an active LoRa network utilizing an ESP32 LoRa SX1276 module, showcasing its compatibility in real-world scenarios.

The recently popularized ISAC paradigm attempts carry out both communication and sensing functionalities uses the same time-frequency resources to combat the scarcity of these resources. However, high-resolution range and velocity radars require wideband long-duration transmission, which implies complex, costly receivers to sample at a high-frequency rate. In this paper, we propose an orthogonal time-frequency space (OTFS)-based ISAC system which enables achieving highly accurate range-velocity profiles without the need for large bandwidth transmissions or long-duration frames. This approach relaxes the constraints on bandwidth and time while still providing precise sensing information. The proposed scheme exploits a single OTFS carrier with rectangular pulse shaping as a pilot to estimate both simultaneous accruing delay and Doppler, thereby determining range and velocity, respectively. By leveraging the sidelobes of the physical pulse shape of the pilot signal, we propose an algorithm that allows the detection of the range and the velocity of radar targets beyond the resolution limitation set by the time duration and the bandwidth of the transmitted signal. The conducted simulation results along with the real experimental results demonstrate that the proposed design can achieve accurate low-complexity radar parameter estimation.