Maximum Likelihood Detection Research Articles

Layered Molecular Shift Keying for Molecular Communication via Diffusion

Molecular communication (MC) is a promising communication paradigm for realizing nano-networks, where molecules are employed as an information carrier. In this letter, based on diffusive MC we propose a novel modulation scheme, called layered molecular shift keying (LMoSK), where several types of molecule form different layers to encode information bits, which can not only improve the data rate but also reduce the effect of inter-symbol interference (ISI). For detection of LMoSK, we formulate an ideal maximum likelihood (ML) receiver assuming knowledge of the ISI. Considering the limited capability of the receiver, we further propose a practical ML detection, enjoying both reduced computational complexity and memory of the receiver. The error performance of the LMoSK with practical ML receiver is analyzed and compared with that of molecular shift keying modulation and molecular type permutation shift keying modulation. Simulation results demonstrate that the proposed LMoSK outperforms benchmark schemes.

Performance Analysis of OTFS Under In-Phase and Quadrature Imbalance at Transmitter

The influence of in-phase and quadrature (IQ) imbalance on the performance of orthogonal time frequency space (OTFS) transmission is investigated in this work. OTFS is a recent two-dimensional transmission scheme with promising robustness against the time and frequency selectivity of the time-varying wireless channel, and IQ impairment arises from inevitable imperfections between in-phase and quadrature branches in the transceiver design. In this paper, the mathematical model is presented to illustrate the physical effect of the IQ mismatched transmitter in OTFS, which results in a new type of interference named mirror-Doppler interference (MDI), occurring only along the Doppler axis. Moreover, a closed-form expression for the average bit error rate (BER) of OTFS with IQ imbalanced transmitter is derived taking into account M-ary symbol with a constant envelope and maximum likelihood (ML) detection principle. Importantly, our findings prove that IQ imbalanced transmitter causes a significant reduction in the diversity gain of OTFS transmission, but does not lead to an error floor in the BER performance as in one-dimensional current communication systems. Monte-Carlo simulations are provided to validate the derived mathematical formulas for OTFS transmission with constant envelope M-ary symbols under different system configurations.

Multi-User Joint Maximum-Likelihood Detection in Uplink NOMA-IoT Networks: Removing the Error Floor

The Internet of Things (IoT) framework requires a massive number of connection thus demanding spectral efficient solutions such as Non-Orthogonal Multiple Access (NOMA). However, the main drawback of NOMA with successive interference canceler (SIC)-based detectors is the error floor in the uplink. In this letter, a reliable multi-user detection in uplink IoT NOMA is guaranteed by a Joint Maximum-Likelihood (JML) detector (i.e., optimum detection algorithm). We derive a closed-form upper bound of bit error rate (BER) of JML over Rayleigh fading channels for arbitrary number of IoT devices and an adaptive M-ary phase shift keying (M-PSK). Based on the extensive simulations, the derived expressions are validated and it is revealed that the JML improves the error performance in uplink NOMA and removes the error floor. Furthermore, regardless of the number of the IoT devices and modulation order, a full diversity order (i.e., number of receiving antennas) is guaranteed for each device.

Optical Wireless Communications Using Signal Space Diversity with Spatial Modulation

A signal space diversity (SSD) scheme was proposed to be incorporated with spatial modulation (SM) in an intensity-modulation/direct-detection-based multiple-input-single-output (MISO) indoor optical wireless communication (OWC) system to improve bit-error-rate (BER) performance and system throughput. SSD was realized via signal constellation rotation and diversity interleaving using different channel gains to improve the BER. With SM incorporated, the MISO-OWC system throughput increased. Theoretical BER expressions of the SSD scheme were established for the first time by investigating the distance of neighboring constellation symbols upon maximum-likelihood detection. Such BER expressions were further verified by numerical results. The results showed that, except for the slightly-lower-accuracy performance brought by comparable distances of neighboring constellation symbols in cases of low signal-to-noise ratios, these BER expressions were accurate in most scenarios. Moreover, theoretical investigations of channel gain distributions were performed at different signal constellation rotation angles to show the capability of the SSD scheme to improve the BER. The results showed that a significantly improved BER by two orders of magnitude could be achieved using a reasonably high channel-gain ratio and a larger constellation rotation angle. The SSD-SM scheme provides a promising option to achieve transmitter diversity with an enhanced throughput in high-speed indoor OWC systems.

Double generalized spatial modulation

AbstractIn this article, motivated by the enhanced spatial modulation and quadrature spatial modulation (QSM) systems, we proposed a new design of double generalized spatial modulation (DGSM), which further exploits the spatial domain not only for the transmission of more extra information bits by increasing the number of antenna index (AI) vectors in an AI vector set, but also for the achievable transmit diversity gain. In DGSM system, we first design the in‐phase and quadrature AI vector sets, whose each AI vector having one or more than one nonzero element equaling to “1” is used for the activation of one or more than one transmit antenna. Then, a spatial antenna index vector (SIV) is generated by adding an AI vector from the in‐phase AI set and another AI vector from the quadrature AI set. Furthermore, a data symbol (eg, QAM/PSK) is modulated on the SIV for forming multiple versions of the data symbol and then transmitted, the maximum likelihood (ML) and sphere decoder (SD) algorithm are applied for the DGSM system. Finally, the performance analysis, including in the spectral efficiency, the computational complexity comparison between the DGSM system with SD algorithm and the diversity‐achieving QSM (DA‐QSM) with ML detector, are provided. Also, the average bit error probability is analyzed. Simulation results using Monte Carlo are presented to show the improvement of bit error ratio performance in comparison with DA‐QSM and other spatial modulation schemes.

Low complexity deep learning algorithms for compensating atmospheric turbulence in the free space optical communication system

One of the main barriers of free space optical (FSO) communication systems is atmospheric turbulence. Various processing techniques at the transmitter, receiver, and transceiver sides are available for addressing this issue; however, they have either high complexity or low performance. Considering this problem, in this study, deep learning (DL) is deployed at the transmitter, receiver, and transceiver sides of an FSO system for constellation shaping, detection, and joint constellation-shaping detection, respectively. Furthermore, the proposed DL-based structures are deployed in an FSO-multi-input multi-output (MIMO) system. As the first investigation over DL for the FSO-MIMO system, different combining schemes including the maximum ratio combiner, equal gain combiner, and the selection combiner are considered. Considering a wide range of atmospheric turbulence, from the weak to the strong regime, the performance of the proposed structures are compared with that of the maximum likelihood (ML) detection. To the best of the authors' knowledge, the main contributions and novelties of this work include considering transmitter learning in the FSO system, designing low complexity DL structures for FSO system applications, and providing complexity analysis for the proposed DL algorithms. The results indicate that the proposed DL-based FSO systems achieve the optimum performance with lower complexity compared with the state-of-the-art conventional FSO systems. For instance, the proposed DL-based detector is almost 2, 3, and 7.5 times faster than the ML detector for modulation orders of 16, 64, and 256, respectively.

Performance analysis of RIS-assisted SM with I/Q imbalance

The idea of utilizing reconfigurable intelligent surfaces (RISs) that employ an array of severally-controllable meta-material elements to scatter incoming data in a desirable way, in wireless communication systems has created new opportunities for transmission in various scenarios. For instance, RISs are envisioned as potential candidates to achieve smart radio environments in fifth generation (5G) network technology, which is usually described as incapable of controlling the environment. Nevertheless, existing studies analyzing RIS-empowered wireless networks generally discuss the cases with ideal hardware despite the fact that both physical transceiver and RISs suffer from unignorable hardware imperfections, which may exceedingly reduce the system performance in practical communication scenarios. This paper investigates the performance of an RIS-assisted spatial modulation (SM) scheme in the presence of in-phase/quadrature-phase imbalance (IQI) at the base station (BS) constituting a substantial impairment in direct-conversion transceivers. The concept of the RIS-assisted SM scheme is discussed by comparing three different implementation scenarios depending on the awareness of both the channel phases at the RIS and the severity of the IQI at the destination (D). The average bit error rate (ABER) is derived analytically by use of maximum likelihood (ML) detection method to tackle the distorting impact of the IQI taking the effects of path loss into account. Extensive computer simulation results, which verify theoretical findings, show that the performance of the traditional SM schemes with IQI can remarkably be improved by utilizing RISs, while having the knowledge of the adjusted phases at the receiver (Rx) provides substantial gain in terms of energy.

Novel detection schemes for generalized quadrature spatial modulation

SummarySpatial Modulation (SM) is a technology that incorporates digital modulation and coding with multiple antennas to achieve high data rates along with improved energy efficiency. Quadrature spatial modulation (QSM), which extends the transmitted signals to in‐phase and quadrature domains, has recently been proposed to improve spectral efficiency (SE) for SM. In this paper, we have considered a combination of Generalized QSM (GQSM) and Quasi Orthogonal Space Time Block Codes (QOSTBC). We propose a new detection scheme for the GQSM and use three different prevailing detection schemes for QOSTBC. We present Bit Error Rate (BER) versus average SNR performance for the combined system using M‐QAM constellations with quasi‐static spatially uncorrelated Rayleigh fading channels and computational complexity in terms of numbers of addition/multiplication and search time. We have compared the considered system with prevailing GQSM system and shown that the prevailing system, as per active antenna permutation (AAP) in GQSM, offers number of transmitted bits ranging from 2 to 9 whereas the proposed system offers number of transmitted bits ranging from 6 to 16 in the same bandwidth. Thus, there is a visible gain in SE. Furthermore, we have compared the BER performance of the considered system with the performance of maximum likelihood detector (MLD) and spatial modulation (SM). In the considered system, the QOSTBC improves the diversity gain. Hence, we have shown that the considered Scheme 3 substantially outperforms the SM. Further, the considered system with Scheme 3 has nearly similar BER performance with the maximum likelihood detector (MLD), which has higher computational complexity.

OFDM-Based Generalized Optical MIMO

The combination of multiple-input multiple-output (MIMO) transmission and orthogonal frequency division multiplexing (OFDM) modulation has been shown to be an effective way to substantially enhance the capacity of bandlimited optical wireless communication (OWC) systems. In this paper, we propose four OFDM-based generalized optical MIMO (GO-MIMO) techniques for intensity-modulation and direct-detection OWC systems, including OFDM-based frequency-domain generalized spatial modulation (FD-GSM), frequency-domain generalized spatial multiplexing (FD-GSMP), time-domain generalized spatial modulation (TD-GSM) and time-domain generalized spatial multiplexing (TD-GSMP). For OFDM-based FD-GSM and FD-GSMP, spatial mapping is performed in the frequency domain, while it is carried out in the time domain for OFDM-based TD-GSM and TD-GSMP. To efficiently estimate both spatial and constellation symbols in each OFDM-based GO-MIMO technique, a corresponding maximum-likelihood (ML) detection algorithm is designed. Extensive simulations are conducted to evaluate and compare the performance of OFDM-based GO-MIMO techniques under various MIMO settings in a typical indoor environment. Simulation results demonstrate that there exists an optimal GO-MIMO technique to achieve a target spectral efficiency for a given receiver location, and the obtained optimal GO-MIMO technique is also related to the specific location of the receiver.

Sparse Code Multiple Access Over Universal Filtered Multicarrier

In this paper, the uplink sparse code multiple access over universal filtered multicarrier (SCMA-UFMC) is studied. In SCMA-UFMC, each sub-band of UFMC is occupied by multiple users through SCMA. Note that the even-component of frequency domain (FD) received signal suffers from neither inter-sub-band interference nor inter-sub-carrier interference while the odd-component suffers from both. The message passing algorithm (MPA) is first employed to perform multiuser detection by utilizing only the even-component. Next, to improve the performance, the odd-component is further utilized. In this improvement, reliable estimates obtained by MPA over even-component are reconstructed and cancelled from odd-component, and then only a very small number of most-unreliable user data are refined by maximum likelihood method. Moreover, the union bound of the average symbol error probability (ASEP) of maximum likelihood detection using only even-component is derived, from which it is shown that ASEP is sub-band-independent. Finally, simulation results are given to demonstrate the performance of the proposed scheme and the effectiveness of the analytical ASEP result.

Performance Analysis of Spectrally Efficient Adaptive Spatial Modulation in MIMO System by using QAM

Abstract: In this article, we proposed a multiple input multiple outputs (MIMO) technique such as spectrally efficient adaptive quadrature spatial modulation (SEAQSM) which is based on space modulation techniques (SMTs). SMTs are logarithmically proportional to transmitting antenna & this technique fulfills the requirement of high data rate in the MIMO system. The Spatial position of the transmitting antenna improves the performance of the MIMO system. In space modulation technique spectral efficiency is logarithmically proportional to transmit antenna, if we increase the antenna at the transmitter end then the bandwidth efficiency significantly improved. We have to improve the performance MIMO system, minimize the latency and low power consumption. The proposed technique performance is explored over Rayleigh fading channel for a particular MIMO. These techniques underestimate the transmit antennas with less RF chain. In this paper, we analyzed the performance of our proposed scheme with conventional SM and QSM by using MONTE CARLO Simulation in term of BER with distinct order of QAM symbol. SE acquired for varying SNR at a BER of 10−3are obtained for uncorrelated Rayleigh channel. Keywords: Spatial Modulation(SM), MIMO, Spectral efficiency, Energy efficiency, Quadrature Spatial Modulation (QAM), Maximum Likelihood (ML) detector.

Carrier Diversity Incorporation to Low-Complexity Near-ML Detection for Multicarrier Systems over V2V Radio Channel.

Inter-carrier interference (ICI) in vehicle to vehicle (V2V) orthogonal frequency division multiplexing (OFDM) systems is a common problem that makes the process of detecting data a demanding task. Mitigation of the ICI in V2V systems has been addressed with linear and non-linear iterative receivers in the past; however, the former requires a high number of iterations to achieve good performance, while the latter does not exploit the channel’s frequency diversity. In this paper, a transmission and reception scheme for low complexity data detection in doubly selective highly time varying channels is proposed. The technique couples the discrete Fourier transform spreading with non-linear detection in order to collect the available channel frequency diversity and successfully achieving performance close to the optimal maximum likelihood (ML) detector. When compared with the iterative LMMSE detection, the proposed system achieves a higher performance in terms of bit error rate (BER), reducing the computational cost by a third-part when using 48 subcarriers, while in an OFDM system with 512 subcarriers, the computational cost is reduced by two orders of magnitude.

Multi-Symbol Digital Signal Processing Techniques for Discrete Eigenvalue Transmissions Based on Nonlinear Fourier Transform

Optical communications based on Nonlinear Fourier Transform (NFT) and digital coherent transceivers are proposed as a new theoretical framework for communications over the nonlinear optical fiber channel. For discrete eigenvalue transmissions (or soliton transmissions), one seeks to encode as much information as possible in each degree of freedom and shorten the distance between neighboring pulses to increase the overall bit rate. However, such attempts would result in nonlinear inter-symbol interference (ISI) across multiple symbols and significantly degrade transmission performance. In this paper, we investigated joint modulation of discrete eigenvalue λ and <b xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">b</b> -coefficents <b xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">b</b> (λ) and developed a suite of multi-symbol digital signal processing (DSP) techniques to exploit the statistical correlations between the continuous and discrete eigenvalues and <b xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">b</b> -coefficents to mitigate nonlinear distortions and improve detection performance. This include 1) jointly modulating both λ and <b xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">b</b> (λ) of pairs of 1-solitons so that the mean value of λ for solitons with odd index is α + 1 <b xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i</b> while it is - α + 1 <b xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i</b> for solitons with even index. This is followed by decoding superimposed received waveforms as 2-solitons with twice the INFT processing time window; 2) linear minimum mean squared error (LMMSE) estimation filters to mitigate noise in discrete eigenvalue λ using continuous eigenvalue; 3) multi-symbol (MS) LMMSE filters to mitigate noise in <b xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">b</b> (λ) using discrete eigenvalue noise and 4) approximate the received signal distributions of λ and <b xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">b</b> (λ) as Gaussians with mean and covariance matrices obtained empirically from experiments followed by Maximum Likelihood (ML) detection for each symbol or multi-symbol (MS)-joint ML detection of 2-soliton signals. We jointly modulate λ with 16-QAM and <b xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">b</b> (λ) with 16-APSK and a record single-polarization discrete eigenvalue transmission of 64 Gb/s (net 54 Gb/s) over 1200 km is experimentally demonstrated with the proposed multi-symbol DSP algorithms.

Low Complexity Quasi-Optimal Detector for Generalized Spatial Modulation

Generalized Spatial Modulation (GSM) is a promising technique for high data-rates systems where the complexity of the optimal joint detector based on the Maximum Likelihood (ML) criterion increases dramatically in terms of the modulation order and the number of activated transmit antennas. In this letter, a novel detection scheme for GSM systems denoted by O <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> SIC-ML is proposed to achieve the optimal performance with a controllable complexity-performance trade-off. The proposed detector is accompanied with ordering techniques for the transmit antenna combination and symbols to further reduce the complexity and improve the performance, respectively. The result reveals that O <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> SIC-ML allows reaching the non-linear ML detector performance with a 99% complexity reduction.

OFDM with Double Spatial Modulation for Improving the Reliability of Wireless Communication

Orthogonal frequency division multiplexing with index modulation (OFDM-IM) has recently attracted numerous research interests, which enhances the spectral efficiency and the reliability of wireless communication by well transplanting the core idea of spatial modulation (SM) into the OFDM system such as the index of subcarrier. Due to that double spatial modulation (DSM) improves the spectral efficiency and the uncoded bit error rate (BER) as compared with SM, in this paper, a new design of OFDM with DSM (OFDM-DSM) is further investigated. Specifically, the design of the OFDM-DSM system is elaborately introduced. Based on the maximum-likelihood (ML) detector, the average bit error probability is presented. Finally, compared to conventional schemes such as OFDM, OFDM-IM, simulation results show that the OFDM-DSM system has better BER performance than other schemes over Rayleigh distribution and additive white Gaussian noise (AWGN) in wireless communication network.

Adaptive Reinforcement Learning Framework for NOMA-UAV Networks

We propose an adaptive reinforcement learning (A-RL) framework to maximize the sum-rate for non-orthogonal multiple access-unmanned aerial vehicle (NOMA-UAV) network. In this framework, Mamdani fuzzy inference system (MFIS) supervises a reinforcement learning (RL) policy based on multi-armed bandits (MAB). UAV as learning agent serves an internet of things (IoT) region. It manages an interference affected, channel block for NOMA uplink. Sum-rate, rate outage probability and average bit error rate (BER) for far-user are compared. Simulations reveal superior performance of A-RL, compared to non-adaptive RL counterpart. Joint maximum likelihood detection (JMLD) and successive interference cancellation (SIC) are also compared for BER performance and implementation complexity.

A novel JFG detection-decoding approach of a vertical shuffle scheduling for iterative MIMO receivers with NB-LDPC codes

MIMO systems exploit multi-path propagation in a rich broadcast environment to improve throughput and performance of digital communication systems. The correspondent demappers require additional computational complexity. In this paper, a new detection-decoding approach based on vertical shuffle scheduling is proposed. Space exploration for the maximum likelihood detection is reduced to a dynamic region that surrounds the received symbol. Thus, a dynamic approach is proposed to detect the closest point of the channel observation without calculating all the candidate symbols in a constellation. In addition, a novel method based on EXIT chart study is proposed to find the sufficient number of neighboring points to search around a local minimum and then compute by recursion their Euclidean distances. Compared to the conventional Maximum Likelihood detector, the proposed algorithm allows a reduction in the computational complexity, in terms of number of multiplication, reaching 98%. The simulation results show that the proposed algorithm outperforms the state-of-the-art algorithms like MMSE, sphere decoding, DBTC and DaVinci codes.

Single-FFT Receiver With Pairwise Maximum Likelihood for Layered ACO-OFDM

A single Fourier transform (FFT) receiver with pairwise maximum likelihood (ML) is proposed for layered asymmetrically clipped optical orthogonal frequency division multiplexing (LACO-OFDM). To improve the single-FFT receiver, the pairwise ML detection is made in time domain after a layer diversion in LACO-OFDM. With only one FFT block, the proposed receiver has a low complexity. Simulation results show that the proposed receiver has the better bit error ratio (BER) performance than the conventional iterative scheme for the LACO-OFDM system with 2 layers in additive white Gaussian noise (AWGN) channel. Furthermore, it is proved that compared with the conventional iterative receiver, the proposed receiver is less sensitive to the clipping distortion. As the nonlinearity increased, the proposed scheme can outperform the conventional iterative solution in nonlinearity channel for LACO-OFDM in visible light communications.

Improved Pair-Wise Detections of Differential Quasi-Orthogonal Space-Time Modulation with Four Transmit Antennas

In this paper, we propose new complex and real pair-wise detection for conventional differential space–time modulations based on quasi-orthogonal design with four transmit antennas for general QAM. Since the new complex and real pair-wise detections allow the independent joint ML detection of two complex and real symbol pairs, respectively, the decoding complexity is the same as or lower than conventional differential detections. Simulation results show that the proposed detections exhibit almost identical performance with an optimum maximum-likelihood receiver, as well as improved performance compared with conventional pair-wise detections, especially for higher modulation order.

Machine Learning-based Signal Detection for PMH Signals in Load-modulated MIMO Systems

Phase Modulation on the Hypersphere (PMH) is a power efficient modulation scheme for the load-modulated multiple-input multiple-output (MIMO) transmitters with central power amplifiers (CPA). However, it is difficult to obtain the precise channel state information (CSI), and the traditional optimal maximum likelihood (ML) detection scheme incurs high complexity which increases exponentially with the number of transmitting antennas and the number of bits carried per antenna in the PMH modulation. To detect the PMH signals without knowing the prior CSI, we first propose a signal detection scheme, termed as the hypersphere clustering scheme based on the expectation maximization (EM) algorithm with maximum likelihood detection (HEM-ML). By leveraging machine learning, the proposed detection scheme can accurately obtain information of the channel from a few of the received symbols with little resource cost and achieve comparable detection results as that of the optimal ML detector. To further reduce the computational complexity in the ML detection in HEM-ML, we also propose the second signal detection scheme, termed as the hypersphere clustering scheme based on the EM algorithm with KD-tree detection (HEM-KD). The CSI obtained from the EM algorithm is used to build a spatial KD-tree receiver codebook and the signal detection problem can be transformed into a nearest neighbor search (NNS) problem. The detection complexity of HEM-KD is significantly reduced without any detection performance loss as compared to HEM-ML. Extensive simulation results verify the effectiveness of our proposed detection schemes.