Non-orthogonal Signals Research Articles

Noise Immunity Analysis of Coherent Demodulation of Synchronous Mutually non-Orthogonal Digital Signals with Minimum-Shift Keying

Introduction. With the provision of the necessary level of economic and defense potential of the state, the problem of protection of lines and networks of digital radio is of high importance. There is a need among the set of technical methods to combat the obstacles to choose their rational set, which will ensure the implementation of modern requirements for noise immunity of digital radio links. The purpose of the study and the basis of the article is to analyze the protection of coherent demodulation of a useful digital signals with frequency minimum-shift keying (MSK) under conditions of strong powerful obstacle. Theoretical results. In order to achieve this goal, a number of partial tasks were solved in the article, namely: a functional diagram of a coherent demodulator of synchronous mutually nonorthogonal digital signals with MSK was synthesized; the simulation model of the digital radio line, which operates under the conditions of a powerful MSK-obstacle, is developed, with the implementation on the receiving side of the functional scheme of the coherent demodulator of synchronous mutually nonorthogonal digital signals with MSK; a series of experiments were conducted for a number of signal-to-noise ratios and signal-to-obstacle in the communication channel; the analysis of the interference protection were conducted of coherent reception of a useful digital signals with MSK in conditions of synchronous strong powerful obstacle. Conclusions. In the absence of MSK-obstacle the coherent demodulator of synchronous mutually nonorthogonal digital signals with MSK degenerates into a classical coherent demodulator of MSK-signal. The analysis reception protection of the MSK-signal under conditions of the influence of a powerful MSK-obstacle has shown that in case of exceeding the instantaneous power of MSK-obstacle, more than 7 dB over the instantaneous power of a useful signal, the negative influence on the noise immunity of receiving the latter is close to zero, and the noise immunity of reception is approaching of the coherent reception of the frequency-shift keying signal.

Design and Prototyping of Hybrid Analog–Digital Multiuser MIMO Beamforming for Nonorthogonal Signals

To enable user diversity and multiplexing gains, a fully digital precoding multiple-input-multiple-output (MIMO) architecture is typically applied. However, a large number of radio frequency (RF) chains make the system unrealistic to low-cost communications. Therefore, a practical three-stage hybrid analog-digital precoding architecture, occupying fewer RF chains, is proposed aiming for a nonorthogonal Internet of Things (IoT) signal in low-cost multiuser MIMO systems. The nonorthogonal waveform can flexibly save spectral resources for massive devices connections or improve data rate without consuming extra spectral resources. The hybrid precoding is divided into three stages, including analog domain, digital domain, and waveform domain. A codebook-based beam selection simplifies the analog-domain beamforming via phase-only tuning. Digital-domain precoding can fine-tune the codebook shaped beam and resolve multiuser interference in terms of both signal amplitude and phase. In the end, the waveform-domain precoding manages the self-created intercarrier interference (ICI) of the nonorthogonal signal. This article designs over-the-air signal transmission experiments for fully digital and hybrid precoding systems on software-defined radio (SDR) devices. Results reveal that waveform precoding accuracy can be enhanced by hybrid precoding. Compared to a transmitter with the same RF chain resources, hybrid precoding significantly outperforms fully digital precoding by up to 15.6 dB error vector magnitude (EVM) gain. A fully digital system with the same number of antennas clearly requires more RF chains and, therefore, is low power, space-efficient, and cost-efficient. Therefore, the proposed three-stage hybrid precoding is a quite suitable solution to nonorthogonal IoT applications.

Performance analysis at far and near user in NOMA based system in presence of SIC error

Non-orthogonal multiple access (NOMA) scheme is an emerging 5G technology to improve upon the spectral efficiency. It can support more users than the number of available frequency-,time-, and code-domain resources. The innovation behind NOMA technology is to exploit non-orthogonal resource allocation at the cost of receiver complexity to mitigate the inter-user interference arising due to non-orthogonal signals. In this paper, we present performance analysis of downlink NOMA (DL-NOMA) system in presence of successive interference cancellation (SIC) error over Rayleigh fading channels. In particular, we derive the exact closed-form expressions of bit error rate (BER) at near-user (U1) and far-user (U2) for the considered DL-NOMA system. Besides, we also present the achievable rate analysis of the considered NOMA system and it is observed that its achievable rate is higher as compared to conventional orthogonal multiple access (OMA) schemes. Further, we also determine the optimized power allocation coefficient for the NOMA system. The analytical results are corroborated with the Monte-Carlo simulations. The simulation results are presented for different modulation schemes and for different NOMA scenarios. A close argument between the analytical and simulation results validate our analysis.

G-MultiSphere: Generalizing Massively Parallel Detection for Non-Orthogonal Signal Transmissions

The increasing demand for connectivity and throughput, despite the spectrum limitations, has triggered a paradigm shift towards non-orthogonal signal transmissions. However, the complexity requirements of near-optimal detection methods for such systems becomes impractical, due to the large number of mutually interfering streams and to the rank-deficient or ill-determined nature of the corresponding interference matrix. This work introduces g-MultiSphere; a generic massively parallel and near-optimal sphere-decoding-based approach that, in contrast to prior work, applies to both well- and ill-determined non-orthogonal systems. We show that g-MultiSphere is the first approach that can support large uplink multi-user MIMO systems with numbers of concurrently transmitting users that exceed the number of receive antennas by a factor of two or more, while attaining throughput gains of up to 60% and with reduced complexity requirements in comparison to known approaches. By eliminating the need for sparse signal transmissions for non-orthogonal multiple access (NOMA) schemes, g-MultiSphere can support more users than existing systems with better detection performance and practical complexity requirements. In comparison to state-of-the-art detectors for NOMA schemes and non-orthogonal signal waveforms (e.g., SEFDM) g-MultiSphere can be up to an order of magnitude less complex, and can provide throughput gains of up to 60%.

MOCZ for Blind Short-Packet Communication: Basic Principles

We introduce a novel blind (noncoherent) communication scheme, called modulation on conjugate-reciprocal zeros (MOCZ), pronounced as “Moxie,” to reliably transmit sporadic short-packets over unknown wireless multipath channels. In MOCZ, the information is modulated onto the zeros of the transmitted discrete-time baseband signal’s $z-$ transform, which yields to a codebook of non-orthogonal signals. In the absence of additive noise, the zero structure of the signal is perfectly preserved at the receiver, no matter what the channel impulse response (CIR) is. Furthermore, by a proper selection of the zeros, we show that MOCZ is not only invariant to the CIR but also robust against additive noise. Starting with the maximum-likelihood estimator, we define a low complexity and reliable decoder and compare it to various state-of-the-art noncoherent multipath schemes, such as OFDM index-modulation (IM), OFDM pilot-aided, OFDM differential-modulation, and pulse-position-modulation. Our scheme outperforms all schemes and maintains its performance even if the length becomes shorter than the CIR.

Feasibility analysis of non‐orthogonal waveforms for multiple input multiple output passive radar application

New non-orthogonal multiple access technology is proposed with the development of 5G, which is expected to support higher spectrum efficiency and massive terminal access, it enables the communication system to achieve better bit error rate performance and alleviate the spectrum congestion problem effectively under limited resources. With the design of spectrum sharing for radar and communication getting more attention, 5G non-orthogonal signal has become potential passive radar illumination source. In this article, an orthogonal multiple input multiple output (MIMO) radar waveform design metric by minimising the integration sidelobe level, is introduced firstly. Then based on sparse code multiple access (SCMA) technology, the non-orthogonal waveform is designed as the passive radar illumination sources. The distance and Doppler resolution of non-orthogonal waveform are evaluated by a more generalised MIMO ambiguity function. Simulation results demonstrate that non-orthogonal SCMA signals have competitive performance with orthogonal code division multiple access signals.

Waveform and Space Precoding for Next Generation Downlink Narrowband IoT

Narrowband Internet of Things (NB-IoT) was introduced by 3GPP in low power wide area network to support low power and wide coverage applications. Since it follows long term evolution standard, its signal quality is guaranteed and its deployment is straightforward via reusing existing infrastructures. Current NB-IoT supports low data rate services via using low order modulation formats for the purpose of power saving. However, with the increase of data rate driven applications, next generation NB-IoT would require data rate enhancement techniques without consuming extra battery power. In this paper, a downlink framework, using a nonorthogonal signal waveform for next generation enhanced NB-IoT (eNB-IoT), is proposed and experimentally tested in both single-antenna and multiantenna systems. In the single-antenna scenario, waveform precoding is used to pre-equalize the self-created inter carrier interference distorted signal waveform. For the multiantenna multiuser scenario, both waveform and antenna space precoding have to be used. Measured results show that in both single-antenna and multiantenna systems, the proposed signal waveform in eNB-IoT can increase data rate by ~11% compared with NB-IoT occupying the same spectral resource in similar receiver computational complexity.

Non-Orthogonal Signal Transmission Over Nonlinear Optical Channels

The performance of spectrally efficient frequency division multiplexing (SEFDM) in optical communication systems is investigated considering the impact of fiber nonlinearities. Relative to orthogonal frequency division multiplexing (OFDM), sub-carriers within SEFDM signals are packed closer at a frequency spacing less than the symbol rate. In order to recover the data, a specially designed sphere decoding detector is used at the receiver end to compensate for the self-created inter carrier interference encountered in SEFDM signals. Our research demonstrated the benefits of the use of sphere decoding in SEFDM and also demonstrates the performance improvement of long-haul optical communication systems using SEFDM compared to the use of conventional OFDM, when fiber nonlinearities are considered. Different modulation formats ranging from 4QAM to 32QAM are studied and it is shown that, for the same spectral efficiency and information rate, SEFDM signals allow a significant increase in the transmission distance compared to conventional OFDM signals.

Single-Channel Speech Dereverberation in Noisy Environment for Non-Orthogonal Signals

Single-Channel Speech Dereverberation in Noisy Environment for Non-Orthogonal Signals

DOA Estimation for Multiple Targets in MIMO Radar with Nonorthogonal Signals

This paper addresses the direction of arrival (DOA) estimation problem in the colocated multiple-input multiple-output (MIMO) radar with nonorthogonal signals. The maximum number of targets that can be estimated is theoretically derived as rankRsN, where N denotes the number of receiving antennas and Rs is the cross-correlation matrix of the transmitted signals. Therefore, with the rank-deficient cross-correlation matrix, the maximum number that can be estimated is less than the radar with orthogonal signals. Then, a multiple signal classification- (MUSIC-) based algorithm is given for the nonorthogonal signals. Furthermore, the DOA estimation performance is also theoretically analyzed by the Carmér-Rao lower bound. Simulation results show that the nonorthogonality degrades the DOA estimation performance only in the scenario with the rank-deficient cross-correlation matrix.

Novel Sparse-Coded Ambient Backscatter Communication for Massive IoT Connectivity

Low-power ambient backscatter communication (AmBC) relying on radio-frequency (RF) energy harvesting is an energy-efficient solution for batteryless Internet of Things (IoT). However, ambient backscatter signals are severely faded by dyadic backscatter channel (DBC), limiting connectivity in conventional orthogonal time-division-based AmBC (TD-AmBC). In order to support massive connectivity in AmBC, we propose sparse-coded AmBC (SC-AmBC) based on non-orthogonal signaling. Sparse code utilizes inherent sparsity of AmBC where power supplies of RF tags rely on ambient RF energy harvesting. Consequently, sparse-coded backscatter modulation algorithm (SC-BMA) can enable non-orthogonal multiple access (NOMA) as well as M-ary modulation for concurrent backscatter transmissions, providing additional diversity gain. These sparse codewords from multiple tags can be efficiently detected at access point (AP) using iterative message passing algorithm (MPA). To overcome DBC along with intersymbol interference (ISI), we propose dyadic channel estimation algorithm (D-CEA) and dyadic MPA (D-MPA) exploiting weighted-sum of the ISI for information exchange in the factor graph. Simulation results validate the potential of the SC-AmBC in terms of connectivity, detection performance and sum throughput.

A Joint Update Parallel MCMC-Method-Based Sparse Code Multiple Access Decoder

With the requirement for growth of massive connections in the fifth-generation (5G) system, there is an increasing challenge for traditional multiple access techniques to meet the needs of the exponentially increased number of terminals for the resource constrained networks. The sparse code multiple access (SCMA) technology has been proposed for the 5G communication systems to supply stronger connectivity with limited resources. However, a low-complexity decoding algorithm is required by the SCMA decoder for the high computation complexity of decoding nonorthogonal signals. In this paper, we propose a high-performance and low-cost decoding algorithm based on a Bayesian program learning method, Monte Carlo Markov Chain (MCMC). We also propose a new MCMC sampling method to generate samples from a joint update parallel (JUP) MCMC sampler. The simulation results show that the JUP-based MCMC SCMA decoder can save 60% computation complexity compared to the existing decoding method with a codebook size 16, which only has 0.5-dB performance loss compared to the maximum-likelihood-like decoding algorithm.

Practical Evaluations of SEFDM: Timing Offset and Multipath Impairments

The non-orthogonal signal waveform spectrally efficient frequency division multiplexing (SEFDM) improves spectral efficiency at the cost of self-created inter carrier interference (ICI). As the orthogonal property, similar to orthogonal frequency division multiplexing (OFDM), no longer exists, the robustness of SEFDM in realistic wireless environments might be weakened. This work aims to evaluate the sensitivity of SEFDM to practical channel distortions using a professional experiment testbed. First, timing offset is studied in a bypass channel to locate the imperfection of the testbed and its impact on SEFDM signals. Then, the joint effect of a multipath frequency selective channel and additive white Gaussian noise (AWGN) is investigated in the testbed. Through practical experiments, we demonstrate the performance of SEFDM in realistic radio frequency (RF) environments and verify two compensation methods for SEFDM. Our results show first frequency-domain compensation works well in frequency non-selective channel conditions while time-domain compensation method is suitable for frequency selective channel conditions. This work paves the way for the application of SEFDM in different channel scenarios.

Practical Receiver for Optimal Discrimination of Binary Coherent Signals.

We address the long-standing problem of discriminating coherent states with the minimum error rate. We show an optimum receiver for coherent states which admits a relatively simple implementation with current technologies. The receiver is based on multichannel splitting of the signal, followed by feed-forward signal displacement and photon-counting detection. We develop an optimal control strategy for a finite signal split and show convergence of the error rate to the Helstrom bound.

Sensing in the presence of an observed environment

Sensing in the presence of environmental noise is a problem of increasing practical interest. In a master equation description, where the state of the environment is unobserved, the effect of signal and noise is described by system operators only. In this context it is well-known that noise that is orthogonal on an external signal can be corrected for without perturbing the signal, while similarly efficient strategies for non-orthogonal signal and noise operators are not known. Here we make use of the fact that system-environment interaction typically arises via local two-body interactions describing the exchange of quanta between system and environment, which are observable in principle. That two-body-interactions are usually orthogonal on system operators, allows us to develop error corrected sensing supported by the observation of the quanta that are emitted into the environment. We describe such schemes and outline a realistic proof-of-principle experiment in an ion trap set-up.

Generalized Cramér–Rao Bound for Joint Estimation of Target Position and Velocity for Active and Passive Radar Networks

In this paper, we derive the Cramer-Rao bound (CRB) for joint target position and velocity estimation using an active or passive distributed radar network under more general, and practically occurring, conditions than assumed in previous work. In particular, the presented results allow nonorthogonal signals, spatially dependent Gaussian reflection coefficients, and spatially dependent Gaussian clutter-plus-noise. These bounds allow designers to compare the performance of their developed approaches, which are deemed to be of acceptable complexity, to the best achievable performance. If their developed approaches lead to performance close to the bounds, these developed approaches can be deemed "good enough". A particular recent study where algorithms have been developed for a practical radar application which must involve nonorthogonal signals, for which the best performance is unknown, is a great example. The presented results in our paper do not make any assumptions about the approximate location of the target being known from previous target detection signal processing. In addition, for situations in which we do not know some parameters accurately, we also derive the mismatched CRB. Numerical investigations of the mean squared error of the maximum likelihood estimation are employed to support the validity of the CRBs. In order to demonstrate the utility of the provided results to a topic of great current interest, the numerical results focus on a passive radar system using the Global System for Mobile communication (GSM) cellar system.

Оценивание параметров радиоимпульса с использованием метода максимального правдоподобия

The paper is devoted to the development of an algorithm for resolution and parameter estimation of radio impulses with partially overlapping spectra in the area of their nonorthogonality (the correlation coefficient varies from 0 to 0.9). The implementation of the suggested algorithm makes it possible to design filters for resolving frequency-dependent signals and, therefore, to increase the capacity of a communication channel. The maximum likelihood method has been used to obtain analytical expressions and to perform model investigations for frequency resolution of nonorthogonal signals. The dynamic range of signal parameter estimates has been found as a function of signal-to-noise ratio and correlation coefficient. It has been shown that the likelihood functional value in its global minimum allows one to estimate noise variance and the number of radio impulses in a received signal.

State-discrimination attack on discretely modulated continuous-variable quantum key distribution

The continuous-variable quantum key distribution (CVQKD) schemes with discrete modulation are proposed to allow distributions of secret keys over long distance due to the sharing of discrete data. However, the nonorthogonal signal states in these schemes can be discriminated by using quantum receivers with low error rates, which may incur state-discrimination (SD) attacks. We consider the feasibility of Eve's attacks on discrete-modulated CVQKD protocol based on the SD receiver. In particular, an intercept-resend attack is proposed on the four-state protocol based on an SD receiver and a heralded noiseless linear amplifier. The security analysis shows that the secret key rate inferred by Alice and Bob can be larger than its true value, which reveals that the original four-state protocol is not secure under the SD attack. Fortunately, the decoy states can be well applied to remedy this defect, but with the cost of complicated practical implementation.

An Improved Fixed Sphere Decoder Employing Soft Decision for the Detection of Non-orthogonal Signals

This letter proposes a hybrid soft iterative method together with Fixed Sphere Decoding (FSD) concurrently optimize performance and complexity. We show that for bandwidth compression factors of up to 25 percent, we can achieve the same performance as Orthogonal Frequency Division Multiplexing (OFDM). For systems with bandwidth compression higher than 25 percent, the complexity/performance trade-offs of the hybrid method are better than those of Truncated Singular Value Decomposition-FSD (TSVD-FSD).

Inter-Cell Interference in Noncooperative TDD Large Scale Antenna Systems

In this paper we study the performance of cellular networks when their base stations have an unlimited number of antennas. In previous work, the asymptotic behavior of the signal to interference plus nose ratio (SINR) was obtained. We revisit these results by deriving the rigorous expression for the SINR of both downlink and uplink in the scenario of infinite number of antennas. We show that the contamination of the channel estimates happens whenever a pilot sequence is received at a base station simultaneously with non-orthogonal signals coming from other users. We propose a method to avoid such simultaneous transmissions from adjacent cells, thus significantly decreasing interference. We also investigate the effects of power allocation in this interference-limited scenario, and show that it results in gains of over 15dB in the signal to interference ratio for the scenario simulated here. The combination of these two techniques results in rate gains of about 18 times in our simulations.