Joint Maximum Likelihood Detection Research Articles

Orthogonal waveform-based backscattering interference suppression technique for underwater optical wireless communication

The backscattering effects degrade the detection performance in a full-duplex underwater optical wireless communication (UOWC) system when the power of received backscattering interference is comparable to that of a target signal. In this paper, the orthogonal waveforms with the Hermite–Gaussian function and prolate spheroidal wave function are first introduced for a pulse position modulation based dynamic UOWC system to alleviate the backscattering effects. Then, a joint maximum likelihood detection scheme is proposed accordingly. Experimental results verify the superiority of the proposed method with orthogonal waveforms over the scheme without orthogonal pulse shaping in a dynamic underwater bubbly channel.

Transceiver design for an uplink asynchronous NOMA using MSK-type signals

The time offset is intentionally introduced into non-orthogonal multiple access (NOMA) to decrease inter-user interference and enhance performance. Recently, minimum shift keying type (MSK-type) signals suitable for power-efficient nonlinear amplifiers have been considered into the uplink asynchronous NOMA (ANOMA), but it is only for the capacity analysis. In this paper, the transceiver design for an uplink ANOMA using MSK-type signals is our concern. Following the maximum likelihood (ML) criterion under successive interference cancellation (SIC), we first propose a Viterbi algorithm (VA)-based detector. By the eigenvalue decomposition (ED) of Hermitian-Toeplitz matrices, an ED-based transceiver scheme is also given. Further, considering the asymptotic behavior of banded-Toeplitz matrices and the limitations of SIC-based transceivers, we propose a DFT matrix diagonalization (DFTD)-based transceiver scheme for joint ML (JML) detection. Finally, the complexity analysis of several detectors is provided. Numerical results reveal that the maximum sum throughput can be achieved by setting half the bit interval, and the time offset can bring a performance gain of 4 dB or 7.5 dB for SIC-based transceivers and 8 dB for JML-based transceivers. The relationship between bit-error-rate (BER) performance and different channel differences, and modulation formats is also shown by simulation.

Performance Analysis and Power Allocation for Spatial Modulation-Aided MIMO-LDM With Finite Alphabet Inputs

In this paper, we study a spatial modulation (SM) aided multiple-input multiple-output (MIMO) layered division multiplexing (LDM) system for broadcast/multicast service delivery in future broadcast/multicast systems. Comprehensive performance analysis and the injection level (IL) optimization are investigated for the SM-aided MIMO-LDM system over correlated Rayleigh fading channels. First, the symbol detection pairwise error probability (PEP) and the average symbol error rate (SER) union bound under joint maximum-likelihood (ML) detection are derived. Second, the spectral efficiency (SE) of the SM-aided MIMO-LDM system with finite alphabet inputs is analyzed. Since the theoretical SE lacks closed-form expression and involves prohibitive computational complexity, we then derive the closed-form lower bounds and tight approximations for the theoretical SE, in which the computational complexity is relieved by several orders of magnitude compared to direct calculation of the theoretical SE. Third, based on the SE analysis, a weighted sum (WS) SE maximization problem with quality of service (QoS) constraints is formulated to optimize IL for the SM-aided MIMO-LDM system. We first demonstrate that WS SE is a unimodal function of IL, and then develop an efficient golden section search (GSS) based algorithm. Simulation results are provided to validate the theoretical analysis. It is shown that our derived SER union bound well matches the simulated SER in the high SNR region. The tightness of the derived closed-form lower bounds and approximations for theoretical SE and the effectiveness of the developed IL optimization algorithm are also verified by simulation results.

A Novel Expectation-Maximization-Based Blind Receiver for Low-Complexity Uplink STLC-NOMA Systems.

In this paper, we revisit a two-user space-time line coded uplink non-orthogonal multiple access (STLC-NOMA) system for Internet-of-things (IoT) networks and propose a novel low-complexity STLC-NOMA system. The basic idea is that both IoT devices (stations: STAs) employ amplitude-shift keying (ASK) modulators and align their modulated symbols to in-phase and quadrature axes, respectively, before the STLC encoding. The phase distortion caused by wireless channels becomes compensated at the receiver side with the STLC, and thus each STA’s signals are still aligned on their axes at the access point (AP) in the proposed uplink STLC-NOMA system. Then, the AP can decode the signals transmitted from STAs via a single-user maximum-likelihood (ML) detector with low-complexity, while the conventional uplink STLC-NOMA system exploits a multi-user joint ML detector with relatively high-complexity. We mathematically analyze the exact BER performance of the proposed uplink STLC-NOMA system. Furthermore, we propose a novel expectation-maximization (EM)-based blind energy estimation (BEE) algorithm to jointly estimate both transmit power and effective channel gain of each STA without the help of pilot signals at the AP. Somewhat interestingly, the proposed BEE algorithm works well even in short-packet transmission scenarios. It is worth noting that the proposed uplink STLC-NOMA architecture outperforms the conventional STLC-NOMA technique in terms of bit-error-rate (BER), especially with high-order modulation schemes, even though it requires lower computation complexity than the conventional technique at the receiver.

Error Performance Analysis of Multiuser Detection in Uplink-NOMA With Adaptive M-QAM

This letter provides a generalized performance analysis for the multi-user uplink-NOMA system with adaptive square quadrature amplitude modulation (QAM) over Rayleigh fading channels. Motivated by the massive IoT connections and unavailability of orthogonal resources for each node, we consider a multi-access scheme where multi-users with single-antenna transmit data to a multiple-antenna base station through the same resource block. By taking advantage of combining diversity paths with the proposed joint maximum-likelihood detector (JMLD), a closed form expression for the upper bound of bit error rate (BER) is obtained. Despite the number of users or the order of modulation, the analytical results endorsed via computer simulations reveal the ability of the MRC-JMLD detector to discard the error floor completely. Moreover, the simulation results show that the MRC-JMLD surpasses its counterparts significantly and ensures a full diversity order.

2D Generalized Optical Spatial Modulation for MIMO-OWC Systems

In this paper, a novel two-dimensional (2D) generalized optical spatial modulation (GOSM) scheme is proposed for multiple-input multiple-output optical wireless communication (MIMO-OWC) systems. By grouping multiple successive time slots as one time block, 2D GOSM mapping can be performed not only in the space domain but also in the time domain. Specifically, two types of 2D GOSM mapping schemes are designed, including 2D-1 and 2D-2 GOSM mappings. Moreover, to address the high complexity issue of optimal joint maximum-likelihood (ML) detection and the noise amplification and error propagation issues of zero-forcing-based ML (ZF-ML) detection, a deep neural network (DNN)-aided detection scheme is further designed for 2D GOSM systems. Simulation results demonstrate the superiority of the proposed 2D GOSM scheme with deep learning-aided detection for high-speed and low-complexity MIMO-OWC systems. More specifically, a remarkable 3.4-dB signal-to-noise ratio (SNR) gain can be achieved by 2D GOSM in comparison to the conventional one-dimensional (1D) GOSM, when applying the DNN-aided detection.

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.

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.

MIMO Based Cooperative Communication and Joint Maximum Likelihood Detection for Cognitive Radio System

In this work, novel cooperative communication strategies like Decode and Forward based relay schemes, joint maximum likelihood signal detection in combinational Multiple Input Multiple Output (MIMO) cooperative relay cognitive networks are used. The joint cooperative signal detection using Maximum-Likelihood (ML) detector at each relays, and associated path links improves the quality of services at the destination node, which can be dynamically altered using different relay combinations and associated iterative computational complexity accumulated during ML detection. Here the relay performs ML decoding and transmit the detected symbols to the destination and also to the multiple antennas equipped for cooperative communication. The same ML detection at the destination combines the MIMO based diversity to narrow down the error probability among different orthogonal transmissions. The combination of iterative signal detection and relay assisted decoding scheme shows superior error rate performance when compared to non-iterative hard decoded signal detection. The simulations results proved the influence of MIMO assisted cooperative communication and the associated performance penalty gaps that come with imperfect channel state information at the destination node.

Optimal Linear Detection for MIMO Systems With Finite Constellation Inputs

To realize the high data rates with low complexity in MIMO systems, linear detections are commonly used where the received signal vector is first transformed to a new vector and then detected on per symbol basis. However, the typical linear detectors such as zero forcing detector and minimum mean-square error detector are not optimal in terms of maximizing the achievable data rate of MIMO system under linear detection constraint. In this letter, we investigate the optimal linear transformer that can maximize such rate with finite constellation inputs. By capitalizing on the relationship between mutual information and the MMSE between channel inputs and outputs, the optimal linear detector (OLD) can be expressed as a fixed-point equation and be solved iteratively. Analytical results prove the consistence between the proposed OLD and the joint maximum likelihood detector (JMLD) in the low- and high-SNR region. The further simulation results verify the consistence, and moreover, at moderate SNR, OLD can significantly improve the achievable data rate and is close to that of JMLD.

Non-orthogonal multiple access with joint maximum likelihood detection in heterogeneous network

As one of the key technologies in the fifth-generation mobile communication system, non-orthogonal multiple access (NOMA) has been investigated. In NOMA, multiple terminals are assigned the same frequency resources by a scheduler on the basis of the difference in propagation losses between a base station and user terminals. Each terminal cancels the signals for the other terminals and extracts its desired signal. On the other hand, the application of joint maximum likelihood (ML) detection to overloaded signals has also been investigated, and joint ML detection can be applied to a NOMA downlink. In this paper, the effect of joint ML detection in a heterogeneous NOMA network is presented. The numerical results obtained through system-level simulation show that joint ML detection in a heterogeneous NOMA downlink can effectively offload mobile traffic from a macro base station to a pico base station. It is shown that a heterogeneous NOMA network with joint ML detection improves the throughput performance by 0.2 bit/user/subcarrier as compared to that without joint ML detection at a cumulative probability of 0.5. The system throughput is also increased about twofold with joint ML detection.

Joint Power and Modulation Optimization in Two-User Non-Orthogonal Multiple Access Channels: A Minimum Error Probability Approach

In this paper, we consider the joint power and modulation optimization in two-user non-orthogonal multiple access (NOMA) channels based on error-rate performance criterion and finite-alphabet inputs. Specifically, with joint maximum-likelihood detection being employed at each user's receiver, the users’ transmission power levels are jointly determined with the 4-QAM constellation of one of the users being rotated such that the probability of dominant pairwise error event in the NOMA channel is minimized. Toward solving the joint power and modulation problem, our results are twofold. First, with $M$ antennas at the receiver, closed-form expressions for the optimal angles as a function of $M$ , the channel coefficients, and the users’ power levels are derived. Second, closed-form expressions are derived for the joint power allocation with optimal rotation by casting the joint optimization as a piecewise convex optimization problem over its sub-domains. Using the proposed joint optimization, the error-rate performance of NOMA improves significantly and it outperforms traditional NOMA power allocation methods for the selected transmission rates. The proposed approach thus represents a rather distinct approach in NOMA optimization, and it is applicable in the uplink NOMA where users share the same time/frequency channel or in the downlink NOMA where users are multiplexed in the power domain.

Transmitter-Precoding-Aided Spatial Modulation Achieving Both Transmit and Receive Diversity

We propose and investigate a precoding-aided spatial modulation (PSM) scheme, which can simultaneously achieve transmit and receive diversity and, hence, is referred to as the TRD-PSM scheme. In TRD-PSM systems, information is transmitted jointly using an amplitude-phase modulation and a receive-antenna-based space-shift keying modulation. We consider two types of linear precoders, namely transmitter zero forcing (TZF) and transmitter minimum mean square error (TMMSE), so as to facilitate low-complexity signal detection. In order to satisfy the different requirement for complexity and reliability, we introduce/propose a range of detection algorithms, which include a joint maximum likelihood detector (JMLD), a simplified JMLD, a successive maximum likelihood detector (SMLD), a simplified SMLD, and a ratio-threshold-test-assisted maximum likelihood detector. We address the principles, characteristics, complexity, and performance of these detection algorithms. Furthermore, we analyze the average bit error probability of the TZF- and TMMSE-assisted TRD-PSM systems employing, respectively, the JMLD and the simplified JMLD and at both small and large scales. Finally, numerical and simulation results are provided to demonstrate and compare the achievable performance of TRD-PSM systems employing various precoding and detection algorithms, as well as to validate the formulas derived.

Efficient Transmission and Detection Based on RNS for Generalized Space Shift Keying

We propose an efficient transmission scheme for the generalized space shift keying (GSSK) based on the residue number system (RNS). The proposed scheme increases the number of active transmit antenna combinations (TACs), resulting in a higher throughput than that of the conventional GSSK systems. The received signals can be detected by a joint maximum likelihood (ML) detection, whose complexity, however, grows exponentially with the number of active TACs. To solve this problem, we propose a new detection method based on the RNS, whose complexity is much lower than that of the joint ML detection with negligible performance loss.

Antenna Reliability Ordering Technique for Unequal Error Protection in Jointly Detected MIMO Systems

In this paper, we address the ordering of transmit antennas according to reliability for unequal error protection (UEP) in spatially multiplexed (SM) multiple-input multiple-output (MIMO) systems with joint detection at the receiver. When zero-forcing (ZF) detection is adopted, the reliabilities of transmit antennas are explicitly expressed as postequalization signal-to-noise ratios (SNRs). Thus, multiantenna UEP can be implemented by assigning data of high priority to transmit antennas with a high postequalization SNR. Unfortunately, the overall error performance is generally unsatisfactory. Various joint signal detection techniques that achieve maximum likelihood (ML) or near-ML performance have been developed as alternatives to ZF, but it is not obvious how to discriminate the reliabilities of the transmit antennas or the jointly detected symbols. Recently, an ordering technique for antenna reliabilities was proposed that exploits the structure of the previous near-optimal QR-decomposition-based least-reliable-layer joint detection. In this paper, we divide the log-likelihood ratio of each symbol into collaborative and individual components, assuming joint ML detection. We derive a statistical connection between the magnitude order of each component of the multiple symbols (or the corresponding transmit antennas) and the post-ZF-equalization SNRs. Based on the statistical connections, we propose the use of post-ZF-equalization SNR as a criterion for antenna reliability ordering of SM MIMO with various near-optimal, as well as optimal, joint detections. The differentiated error performance of transmit antennas is also shown to be mainly attributed to the difference of individual components, and the tendency becomes stronger as the constellation size increases. Simulations demonstrate that the proposed ordering technique better meets the UEP requirement with lower computational complexity than the conventional ordering. Assuming $N_t \times N_t$ MIMO systems, the previous ordering and the proposed ordering require $\mathcal{O}(N_t^3)+\sum_{N=2}^{N_t-1}\mathcal{O}(NN_t^2+N^3)$ and $\mathcal{O}(N_t^3)$ , respectively.

Joint Maximum Likelihood Detection in Far User of Non-Orthogonal Multiple Access

Joint Maximum Likelihood Detection in Far User of Non-Orthogonal Multiple Access

Joint Multiuser Detection of Multidimensional Constellations over Fading Channels

We investigate the error performance of multidimensional constellations in the multiple access and broadcast channels. More specifically, we provide closed-form expressions for the pairwise error probability (PEP) of the joint maximum likelihood detection, for multiuser signaling in the presence of additive white Gaussian noise and Rayleigh fading. Arbitrary numbers of users and multidimensional signal sets are assumed, while the provided formula for the PEP is a function of the dimension-wise distances of the multidimensional constellation. Furthermore, a useful upper bound on the average symbol error probability is also obtained through the union bound. The analysis is applied to the sparse code multiple access systems. The analytical results are validated successfully through simulations, and show their importance in the multidimensional constellation design.

Compressed Sensing Improves the Performance of Subcarrier Index-Modulation-Assisted OFDM

In orthogonal frequency division multiplexing relying on subcarrier index modulation (OFDM-SIM), the information is conveyed by both the indices of the activated subcarriers and the conventional amplitude-phase modulated (APM) symbols. It has been shown that OFDM-SIM is capable of striking a tradeoff between the attainable spectral efficiency (SE) and energy efficiency (EE). In order to further increase the EE of the OFDM-SIM system, while potentially increasing its SE, we propose a compressed sensing (CS)-assisted signaling strategy for the family of OFDM-SIM systems. Correspondingly, we first consider the joint maximum likelihood detection of the CS-assisted index-modulated (CSIM) and of the classic APM symbols, despite its high complexity. Then, we propose a low complexity detection algorithm, which is termed as the iterative residual check (IRC)-based detector. This is based on the greedy pursuit concept of CS, which makes locally optimal choices at each step. Finally, both analytical and simulation results are provided for characterizing the attainable system performance of our proposed OFDM-CSIM system. We demonstrate that in comparison to the conventional OFDM-SIM system, the proposed OFDM-CSIM arrangement is capable of achieving both a higher SE as well as an increased EE. We also show that the diversity gain provided by the OFDM-CSIM system is much higher than that of the OFDM-SIM system. Furthermore, our investigation of the detection performance shows that the proposed IRC detector is capable of providing an attractive detection performance at a low complexity.

Low Complexity Metric for Joint MLD in Overloaded MIMO System

This paper presents a low complexity metric for joint maximum-likelihood detection (MLD) in overloaded multiple-input multiple-output (MIMO)-orthogonal frequency division multiplexing (OFDM) systems. In overloaded MIMO systems, a nonlinear detection scheme such as MLD combined with error correction coding achieves superior performance than that of a single signal stream with higher order modulation. However, MLD demands large computational complexity because of multiplications in the selection of candidate signal points. Thus, a Manhattan metric has been used to reduce the complexity. Nevertheless, it is not accurate and causes performance degradation in overloaded MIMO systems. Thus, this paper proposes a new metric that is calculated with summations and bit shifts. New numerical results obtained through computer simulation show that the proposed metric improves bit error rate (BER) performance more than 0.2dB at the BER of 10^(-4) in comparison with a Manhattan metric.

Constellation constrained multiuser multiple‐input multiple‐output for high capacity and error performance over correlated fading channels

AbstractChannels' correlation has direct impact to degrade the capacity and reliability of multiple‐input multiple‐output (MIMO) systems considerably. In this paper, new signal constellation designs are investigated to mitigate fading correlation and maximize the capacity and error performance of multiuser MIMO (MU‐MIMO) over correlated channels, which is a major research challenge. Two methods are studied in a novel constellation constrained MU‐MIMO approach, namely, unequal power allocation and rotated constellation. Based on principles of maximizing the minimum Euclidean distance (dmin) of composite received signals, users' data can be recovered using maximum likelihood joint detection irrespective of correlation values. Compared with the identical constellation scenario in conventional MU‐MIMO, it is shown that constellation rearrangement of transmitted signals has direct impact to resolve the detection ambiguity when the channel difference is not sufficient, particularly in moderate to high correlations. Extensive analysis and simulation results demonstrate the superiority of proposed technique to capture most of the promised gains of multiantenna systems and application for future wireless communications. Copyright © 2014 John Wiley &amp; Sons, Ltd.