Noncoherent Detection Research Articles

Transceiver for Ultrasonic Intra-Body Area Networks With Non-Coherent BPSK Detection

Transceiver for Ultrasonic Intra-Body Area Networks With Non-Coherent BPSK Detection

Radar non-coherent integration detection for high- speed multiple targets via Doppler frequency compression

Radar non-coherent integration detection for high- speed multiple targets via Doppler frequency compression

FSK/ASK Orthogonal Modulation System Based on Novel Noncoherent Detection and Electronic Dispersion Compensation for Short-Reach Optical Communications

We propose an FSK/ASK orthogonal modulation system based on a novel noncoherent detection (NCD) scheme, aimed at expanding the system capacity for short-reach optical communications cost-effectively. In the transmitter, the FSK optical signal is generated by simple frequency modulation through a directly modulated distributed feedback laser. Subsequently, by utilizing a Mach–Zehnder modulator for ASK modulation, the FSK/ASK optical signal is obtained. The novel and low-complexity NCD receiver consists of an intensity detection branch and a frequency detection branch. The frequency detection branch is composed of an optical differentiator, a photodetector, and frequency extraction circuits. Notably, the proposed NCD scheme overcomes the limitation of the traditional FSK/ASK-NCD receiver stemming from the trade-off between the detected signal quality of the amplitude and frequency. Furthermore, electronic dispersion compensation (EDC) is available. Through numerical simulations, our findings demonstrate that the proposed FSK/ASK-NCD system, assisted by EDC, achieves a remarkable 100 km transmission span for both 40 Gbps 2FSK/2ASK and 60 Gbps 2FSK/4ASK modulation formats, which surpasses the 2ASK-DD and the 4ASK-DD systems, where the maximum achievable spans are limited to less than 20 km. These results underscore the potential of the proposed system as a robust candidate for future passive optical access networks.

Distributed Learning Over a Wireless Network With Non-Coherent Majority Vote Computation

In this study, we propose an over-the-air computation (OAC) scheme to calculate the majority vote (MV) for federated edge learning (FEEL). With the proposed approach, edge devices (EDs) transmit the signs of local stochastic gradients, i.e., votes, by activating one of two orthogonal resources. The MVs at the edge server (ES) are obtained with non-coherent detectors by exploiting the accumulations on the resources. Hence, the proposed scheme eliminates the need for channel state information (CSI) at the EDs and ES. In this study, we analyze various gradient-encoding strategies through the weight functions and waveform configurations over orthogonal frequency division multiplexing (OFDM). We show that specific weight functions that enable absentee EDs (i.e., hard-coded participation with absentees (HPA)) or weighted votes (i.e., soft-coded participation (SP)) can substantially reduce the probability of detecting the incorrect MV. By taking path loss, power control, cell size, and fading channel into account, we prove the convergence of the distributed learning for a non-convex function for HPA. Through simulations, we show that the proposed scheme with HPA and SP can provide high test accuracy even when the time-synchronization and the power control are not ideal under heterogeneous data distribution scenarios.

Multi-Level Design for Multiple-Symbol Non-Coherent Unitary Constellations for Massive SIMO Systems

This paper investigates non-coherent detection of single-input multiple-output (SIMO) systems over block Rayleigh fading channels. Using the Kullback-Leibler divergence as the design criterion, we formulate a multiple-symbol constellation optimization problem, which turns out to have high computational complexity to construct and detect. We exploit the structure of the formulated problem and decouple it into a unitary constellation design and a multi-level design. The proposed multi-level design has low complexity in both construction and detection. Simulation results show that our multi-level design has better performance than traditional pilot-based schemes and other existing low-complexity multi-level designs.

A New Index Modulation for LoRa

LoRa (Long Range) is a widely adopted Internet-of-Things (IoT) technique, but its fatal limit is a low data rate. In this letter, we propose a new index modulation for LoRa to increase the data rate, in which multiple quasi-orthogonal chirps modulated under different spreading factors (SFs) are concurrently transmitted, thereby leveraging the SF domain as a means to carry more information. Both coherent and non-coherent detection algorithms for the proposed index modulation are also developed in efficient forms. Numerical results demonstrate that the proposed scheme notably outperforms the state-of-the-art techniques.

Diversity-Based Non-Coherent Signal Detector for Molecular Communication via Reaction-Diffusion

Molecular communication is attractive to the emerging nano-scale communication systems. Traditionally, a detector recovers the information from only the concentration of single messenger molecule, while ignoring the variation of multiple participants in biochemical reaction. In this paper, we propose a non-coherent signal detector, by fully exploiting this ubiquitous biochemical diversity property of multiple reacting molecules. After extracting the channel state information (CSI) independent non-coherent features of received signals, the dynamical transient characteristics of messenger, reactant and product molecules are all utilized to implement the diversity detection, thus formulating a functional single-input multiple-output (SIMO) system via reaction-diffusion communication that has been barely considered before. We design both hard and soft combination strategies to attain the potential diversity gain arise from the dynamical co-variation of participants. Theoretical analysis and numerical simulations are provided to demonstrate the advantages of our detector. Compared with conventional detectors that use only single messenger molecule, the bit error rate (BER) of is substantially reduced. Moreover, the BER performances of our non-coherent detector are even better than coherent maximum a posteriori (MAP) detector that requires accurate CSI estimation, which confirms the dramatic diversity gain provided by our detector. It would have great potentials in reliable nano-scale communications.

Approximate BER Performance of LoRa Modulation With Heavy Multipath Interference

This letter proposes a method to approximate LoRa performance over heavy multipath channels. Firstly, the multipath time delay and LoRa signal duration are combined to analyze the path overlapping interference quantitatively. Then simple BER approximations in coherent and non-coherent detections are derived with Gaussian Q-function and algebraic formulas. With the heavy multipath channel model in 3GPP to mimic the realistic indoor industrial scenarios, the approximate expressions are verified by Monte Carlo simulations. Moreover, performance comparison results show that a high spreading factor leads to severe multipath overlap and may result in BER reduction.

Evaluation of Non-Coherent Signal Detection Techniques for Mobile Molecular Communication.

In recent years, there have been more and more research on molecular communication (MC). Because the deployment of mobile nanomachines may be required in some applications of MC, research on mobile MC has become a trend. The signal detection schemes for static MC are no longer applicable due to the time varying channel impulse response (IR), which is caused by the mobile characteristics of nanomachines. In this paper, a low complexity and non-coherent detection scheme is proposed for mobile scenario, which is based on the energy difference between two adjacent symbols. Most of the existing signal detection methods do not consider inter-symbol interference (ISI). Compared with those methods, the proposed scheme can achieve signal detection utilizing ISI without knowing channel state information (CSI). The bit error rate (BER) performance of the proposed method is investigated under different conditions through simulations. Besides, the influence of mobility features of nanomachines on the signal detection accuracy is also investigated in detail. The simulation results demonstrate that the BER performance of the proposed scheme outperforms the latest signal detection scheme for short-distance mobile MC system with high velocity. Consequently, the detection scheme proposed in this paper can reduce the influence of nanomachines' mobility and has the potential to be used in mobile MC systems.

Suppression of Nonlinear Optical Effects in DWDM-PON by Frequency Modulation Non-Coherent Detection

We propose a simple and cost-effective method, using a direct frequency modulation (FM) and noncoherent detection (NCD) scheme, to suppress the nonlinear optical effects in dense wavelength division multiplexed (DWDM) optical communication. The FM transmitter comprises a directly modulated distributed feedback laser and a saturable semiconductor optical amplifier. In the NCD receiver, an optical slope filter as the FM to intensity modulation (IM) signal convertor is placed before a conventional photodetector. Because the FM signal has more evenly distributed optical power, bit-pattern-dependent nonlinear effects are consequently suppressed. After analyzing the nonlinear effects in the FM-NCD system and traditional IM direct detection (IM-DD) system, we found that the minimum achievable BER of the proposed FM-NCD scheme is 40 dB smaller. Moreover, a 2 Tbps (10 Gb/s × 200 channels) capacity was achieved by the FM-NCD system in 100 km DWDM passive optical networks (PONs), which is twice the capacity of the IM-DD system (10 Gb/s × 100 channels) under the same condition. These results indicate that WDM-PONs with the cost-effective FM-NCD scheme are strong candidates for future broad access networks and show great potential for the combination of optical access and metro networks for future generations of PONs.

Joint Coherent and Non-Coherent Detection and Decoding Techniques for Heterogeneous Networks

Cellular networks that are traditionally designed for human-type communication (HTC) have the potential to provide cost effective connectivity to machine-type communication (MTC). However, MTC is characterized by unprecedented traffic in cellular networks, thus posing a challenge to its successful incorporation. In this work, we propose a unified framework for amicable coexistence of MTC and HTC. We consider a heterogeneous network where machine-type devices coexist with enhanced mobile broadband (eMBB) devices and propose transceiver techniques that promote efficient signal recovery from these devices. For this, we present an eMBB pilot and MTC data generation strategy that facilitates joint coherent decoding of eMBB data and non-coherent decoding of MTC data. Furthermore, we assess the feasibility of coexistence using receiver operating characteristics, outage probability, and normalized mean square error (NMSE). Our numerical results reveal that a harmonious coexistence of the heterogeneous services can be achieved with properly configured average signal-to-noise ratios and pilot length.

RIS-Aided Joint Transceiver Space Shift Keying Reflection Modulation

In this letter, a reconfigurable intelligent surface-aided joint transceiver space shift keying reflection modulation (RIS-JTSSK-RM) scheme is proposed. The RIS aids the transceiver SSK modulation and inserts additional bits into the reflected phase shift of the radio frequency (RF) signal simultaneously. The design of reflection modulation constellation points and the joint mapping of transceiver antennas enhance the system’s reliability. To reduce the RIS-JTSSK-RM required computational complexity, a practical non-coherent greedy detector is proposed. In addition, we analyze the proposed system’s bit error rate (BER) performance under the optimal maximum likelihood detector. The theoretical and simulation results show that the proposed system has better BER performance.

Deep Learning-Based Activity Detection for Grant-Free Random Access

The cellular Internet of Things wireless network is a promising solution to provide massive connectivity for machine-type devices. However, designing grant-free random access (GF-RA) protocols to manage such connections is challenging, since they must operate in interference-aware scenarios with sporadic device activation patterns and a shortage of mutually orthogonal resources. Supervised machine learning models have provided efficient solutions for activity detection, noncoherent data detection, and nonorthogonal preamble design in scenarios with massive connectivity. In this article, we develop two deep learning (DL) sparse support recovery algorithms to detect active devices in massive machine-type communication random access. The DL algorithms, developed to deploy GF-RA protocols, are based on the deep multilayer perceptron and the convolutional neural network models. Unlike previous works, we investigate the impact of the type of sequences for preamble design on the activity detection accuracy. Our results reveal that preambles based on the Zadoff–Chu sequences, which present good correlation properties, achieve better activity detection accuracy with the proposed algorithms than random sequences. Besides, we demonstrate that our DL algorithms achieve activity detection accuracy comparable to state-of-the-art techniques with extremely low computational complexity.

A Detection Scheme for Integrated SWIPT Receivers With Rectenna Arrays

Smart devices and their applications led to a rapid evolution of the Internet of Things. As a result, there is an emerging need on energizing those low-power devices, while at the same time achieving information transfer. In this context, simultaneous wireless information and power transfer (SWIPT) is considered as an appealing technology, since it can power wirelessly and remotely such devices, simultaneously with information transfer. Motivated by this, we herein propose a system model with an integrated SWIPT receiver, succeeding enhanced performance in terms of information decoding (ID) and energy harvested (EH). Specifically, we adopt a single input multiple output topology, where at the receiver’s side we examine two antenna architectures, one based on the direct-current (DC) combining and the other on the radio-frequency (RF) combining. For both schemes, we consider multiple receive antennas and rectifiers, comparing their performances. Furthermore, we adopt a piece-wise linear EH model, which takes into account the sensitivity and saturation effects of the rectifiers. By using a maximum likelihood-based soft decoding, a non-coherent energy detection is achieved. Finally, an asymptotic analysis is conducted, providing upper and lower bounds for ID and EH, respectively. Simulation results along with theoretical analysis, validate the enhanced performance both in terms of ID and EH.

A New Noncoherent Gaussian Signaling Scheme for Low Probability of Detection Communications

We propose a novel, Gaussian signaling mechanism for low probability of detection (LPD) communication systems with either single or multiple antennas. The new scheme is designed to allow the noncoherent detection of Gaussian-distributed signals, enabling LPD communications using signals that follow the complex Gaussian distribution in the time and frequency domains. It is demonstrated via simulations that the proposed scheme achieves better performance than a comparable conventional scheme over the entire SNR region, with the advantage becoming more significant in scenarios with lower overhead.

Revisiting Non-Coherent Detection of Differential PSK: A Factor Graph Perspective

For non-coherent differential modulated communications, the multiple-symbol differential detection (MSDD) may approach the coherent detection performance by jointly detecting a block of symbols. However, MSDD cannot support large-size block detection due to its complexity exponentially increasing with the block size. Moreover, MSDD assumes that the channel phase is constant over the symbols in a block, which is not realistic. In this letter, we propose to formulate the signal model of non-coherent differential modulated communications by means of a factor graph. Based on the factor graph, we develop a sum-product message-passing algorithm to enable the maximum a posteriori probability detection. Compared with MSDD, the detection complexity of our proposed scheme is linearly proportional to the block size. Simulation results show that the proposed scheme can not only achieve the performance of MSDD over the constant-phase channel, but also outperform it over the random-walk phase channel.

A robust method for coherent and non-coherent source number detection using a special Hankel-based covariance matrix

A robust algorithm for source number estimation based on the formation of the Hankel covariance matrix is presented. First, multiple data snapshots are taken successively from overlapped subarrays in a way similar to the forward spatial smoothing method to construct the special Hankel covariance matrix and for the total number of subarrays, these special covariance matrices are generated. Then, the average of these matrices is employed in singular value decomposition to generate the corresponding eigenvalues. Finally, the resulting eigenvalues are evaluated via the rule presented in this paper as the Moving Gradient Criterion (MGC) to estimate the number of sources by detection of the largest singular values. The greatest difference between the proposed algorithm and the other conventional methods is the form of the covariance matrix with the observed signal that can handle both non-coherent as well as fully coherent sources. Also, the proposed MGC rule adopted with this form of the covariance matrix is the strength of this work. Numerical simulations demonstrate the high superiority of the proposed approach over the competing methods such as MDL, AIC, SORTE, RAE and MSEE methods, especially in the cases of very closely spaced sources, low SNR values, low sensors number and low snapshots number.

Delay Optimization of Conventional Non-Coherent Differential CPM Detection

The conventional non-coherent differential detection of continuous phase modulations (CPM) is quite robust to channel impairments such as phase and Doppler shifts. Its implementation is on top of that simple. It consists in multiplying the received baseband signal by its conjugate version delayed by one symbol period. However it suffers from a signal-to-noise ratio gap compared to the optimum coherent detection. In this letter, we improve the error rate performance of the conventional differential detection by using a delay higher than one symbol period. We derive the trellis description as well as the branch and cumulative metrics that take into account a delay of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula> symbol periods. We then determine an optimized delay <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$K_{\mathrm {opt}}$ </tex-math></inline-formula> based on the minimum Euclidean distance between two differential signals for some popular CPM formats. The optimized values are confirmed by error rate simulations.

On the Use of FFH-MFSK for Ultra-Low Power Communications in a Jamming Environment

We are interested in a communication system that operates in the presence of an intelligent jammer, under stringent power constraints, but with flexible bandwidth constraints.We optimize some of the key elements in the transceiver design for low power consumption, and thus high complexity components of the system, such as matched filters (MF), forward error correction (FEC) that employs iterative decoders, coherent demodulators, and bandwidth-efficient modulation formats, are not feasible for this research. Rather, our system is designed using <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">M</i> -ary frequency shift keying (MFSK) with non-coherent detection and fast frequency hopping (FFH), optimized two-pole bandpass filters (BPF), and Reed-Solomon (RS) codes with hard-decision decoding. Among other things, we show that by properly optimizing the key parameters of the BPFs and RS codes, we can design the system to be significantly less complex than the MF system with a performance loss of less than 1.4 dB for most scenarios that we considered. Further, the 2-pole BPF system can actually outperform the corresponding MF system by up to 2.4 dB in the presence of multi-tone jamming.

Long-Block Differential Spatial Modulation

Spatial modulation (SM) can transmit additional data bits by selecting antennas and avoids synchronization and interferences among antennas. Differential SM (DSM) is a noncoherent technique of SM, but it is less bandwidth efficient than SM. This paper proposes a novel DSM scheme called long-block DSM (LB-DSM), whose block is longer than the original DSM’s. Each block of LB-DSM consists of two parts. One part is the block of the original DSM, and the other is similar to SM. With the aid of the latter part, the data rate of LB-DSM is higher than that of DSM. Besides, we propose bit mapping and low-complexity noncoherent maximum-likelihood detection for LB-DSM, by which LB-DSM is less complicated than DSM. In addition to higher bandwidth efficiency and lower decoding complexity, distance analysis and computer simulation results indicate that LB-DSM provides better error performance than DSM for 8PSK (eight-ary phase shift keying). Furthermore, the idea of LB-DSM is applied to generalized DSM (GDSM), which activates more than one transmit antenna each time. The resulting scheme, called long-block GDSM, offers better bandwidth efficiency and error performance than GDSM.