Maximum Likelihood Detection Research Articles

RIS-Assisted SSK Modulation: Reflection Phase Modulation and Performance Analysis

In this letter, we present a reconfigurable intelligent surface (RIS)-assisted space shift keying (SSK) modulation and reflection phase modulation (RPM) scheme, where RIS embeds its own information in the reflection phase shift of the reflected radio frequency (RF) signal. More specifically, the RIS simultaneously performs two tasks: i) reflecting the impinging RF signal with a discrete phase shift and ii) embedding the information bits in the phase shift. We perform joint detection for the RPM and SSK symbols using a maximum likelihood detector, and a unified analytical framework is presented for theoretical analysis of the average bit error rate (ABER) and ergodic capacity of the proposed scheme. All numerical results are thoroughly verified through Monte Carlo simulation. Numerical results reveal that the proposed scheme outperforms the conventional SSK scheme.

SSK-ICS LoRa: A LoRa-Based Modulation Scheme With Constant Envelope and Enhanced Data Rate

Long-range (LoRa) modulation is an orthogonal modulation scheme that uses linearly-modulated up chirps to represent information bits. Its constant envelope and good bit-error-rate performance make it one of the key players in establishing low-power wide-area networks for the Internet of things applications. However, LoRa modulation has low data rates. In this letter, we propose a new constant-envelope modulation scheme, named slope-shift-keying and interleaved-chirp spreading (SSK-ICS) LoRa modulation, that can deliver higher data rates than the conventional LoRa modulation scheme. Succinctly, the proposed SSK-ICS-LoRa modulation uses up chirps, down chirps, interleaved up chirps and interleaved down chirps to expand the signal set and hence can carry more bits per transmission symbol. For the same spreading factor and bandwidth consumption, the proposed scheme is able to improve the data rate of the conventional LoRa scheme up to 28.6%. We also present the optimal maximum-likelihood detectors for both coherent and non-coherent demodulators for the proposed scheme. Simulation results show that the proposed scheme outperforms LoRa modulation in both data rate and bit-error rate.

Optimal Spectrum Sensing Threshold for Unequal Priors Case

Classical spectrum sensing techniques utilize maximum likelihood (ML) detection for identification of spectrum holes. The approach is sub-optimal for the case of un-equal priors where the probabilities of channel occupation and vacancy are not the same. Such situations are bound to occur in most commercial bands such as GSM etc and hence are of more interest. The loss in performance has been disregarded as negligible in most of the work done on spectrum sensing techniques. This paper quantifies the effects of changing priors on classical energy detection and infers that the loss in spectrum sensing performance is not negligible. The deterioration is especially considerable at low SNR values and at low probabilities of channel occupation. An optimum threshold for achieving minimum probability of error has been derived in this work for unequal prior case. Detection based on the proposed threshold out-performs classical detectors under the assumption that priors are known at the receiver.

Intelligent conventional and proposed hybrid 5G detection techniques

In recent years, Multiple Inputs and Multiple Outputs (MIMO) have gained significant attention due to their characteristics such as spectral gain, high throughput, and energy efficient. It is seen as one of the integral parts and backbone of the Fifth Generation (5G) and beyond 5G (B5G). However, the use of a large number of antennas requires complex algorithms to detect the received signal. Though, several detection methods have been proposed which can efficiently enhance the Bit Error Rate (BER) gain of the framework, it also increases the computational complexity. The proposed article introduces a hybrid algorithm for different sizes of MIMO. The hybrid algorithm is designed by combining QR Decomposition M−algorithm−Maximum Likelihood Detection (QRM-MLD) and Beam Forming (BF). Further, we compare the performance of proposed hybrid algorithms with that of conventional algorithms, namely Zero Forcing (ZF), Minimum Mean Square Error (MMSE), Successive over Relaxation (SOR), Gauss Seidel Detector (GSD), Jacobi Scheme (JS), and Approximate Message Passing (AMP). In computer simulation, it is noted that the proposed algorithm outperforms the conventional detection algorithms with minimum computational complexity.

Generalized Multistream Spatial Modulation Based on Frequency-Phase Modulated Signals

In this letter, we present an approach to building a new generalized multistream spatial modulation system (GMSM), where the information is conveyed by the two active antennas with signal indices and using all possible active antenna combinations. The signal constellations associated with these antennas may have different sizes. In addition, four-dimensional hybrid frequency-phase modulated signals are utilized in GMSM. Examples of GMSM systems are given and computer simulation results are presented for transmission over Rayleigh and deep Nakagami-<inline-formula> <tex-math notation="LaTeX">$m$ </tex-math></inline-formula> flat-fading channels when maximum-likelihood detection is used. The presented results indicate a significant improvement of characteristics compared to the best-known similar systems.

Low Complexity Optimal and Suboptimal Detection at Spatial Modulation MIMO Receivers

This paper develops three low-complexity detection schemes for the spatial modulation (SM) Multiple Input Multiple Output (MIMO) systems. We first propose a reduced complexity maximum likelihood (RC-ML) detection scheme. For the practical values of the modulation index, the proposed RC-ML method is simpler than the existing hard-limiting-based ML schemes. The two other proposals are based on a suboptimal Maximum Ratio Combining (MRC) detection method. We present a new analysis of the MRC detector in the uncorrelated Rayleigh fading channel and identify the system operational scenarios for which the MRC performance is nearly identical to the ML performance. Our proposals — a hybrid MRC-ML method and an MRC scheme with rank reduction — are inspired by this analysis. The analytical and simulation results show that the proposed MRC-based schemes can attain a near-optimal performance while reducing the complexity of the ML-based SM receiver.

Signal Detection for GSTFIM Systems with Carrier Frequency Offset.

Generalized space-time-frequency index modulation (GSTFIM) inherits the drawbacks of the conventional orthogonal frequency-division multiplex (OFDM), such as being sensitive to carrier frequency offset (CFO). For a robust design against this problem, in this contribution, a novel construction of a message passing (MP)-aided detector is developed for GSTFIM systems to combat the influence of CFO, while offering a flexible tradeoff between transmission performance and computational complexity. Through complexity analysis and simulation results, we demonstrate that, in the context of CFO, with a careful design, the developed MP detector is capable of approaching traditional GSTFIM with maximum likelihood (ML) detection, and of offering better performance at lower complexity compared to its minimum mean-square-error (MMSE)-aided counterpart.

Enhanced generalized space shift keying with search field based iterative MLD for 6G

This paper proposes the novel enhanced generalized space shift keying (EGSSK) to improve the spectral efficiency (SE) and energy efficiency (EE). In conventional GSSK, all of antenna combinations are not used because of power-of-two form. To overcome this problem, we suggest to exploit spare antenna combination for cell-edge users (CEUs). Concurrently, we propose the search field based iterative maximum likelihood detector (SFMLD) to reduce the complexity at the receiver. The simulated and analytical results are shown in terms of SE, average bit error rate (ABER), complexity and EE.

Guest editorial: Smart communications and networking: architecture, applications, and future challenges

Guest editorial: Smart communications and networking: architecture, applications, and future challenges

The impact of intentional interference on the performances of ML detector in MIMO systems

Here we address the problem of performing the resilience of Multiple Input Multiple Output (MIMO) architecture against intentional and unintentional interferences. We investigate the performance of a non-linear receiver based on the Maximum Likelihood (ML) detector in MIMO systems over Gaussian fading channels in the presence of interfering signals. Using the properties of the Gaussian matrix, a finite expression of the Probability Density Function (PDF) for the Signal to Interference plus Noise Ratio (SINR) is obtained as a function of the brute jammer power budget and the number of affected antennas. By considering a particular closed-form of intelligent jamming strategies against MIMO architecture presented in the literature, approximated upper limits of the Bit Error Rate (BER) are performed under different jamming scenarios depending on the Channel State Information (CSI) availability. These results enable us to characterize the consequences of such conflicting attacks on the quality of the legitimate link. Furthermore, extensive simulations are carried out to justify the performance of the ML detector and validate the obtained results.

Ball-Tree-Based Signal Detection for LMA MIMO Systems

In this letter, we consider the uplink multiuser load-modulated array (LMA) multiple-input multiple-output (MIMO) communication system, where multiple users transmit the phase modulation on hypersphere (PMH) signals to a base station (BS). To reduce the detection complexity, we propose a low-complexity detection scheme based on a ball-tree (BT) structure. The received codewords are stored in a space BT data structure and the detection process can be regarded as a nearest neighbor point search operation. Two partition rules are proposed in the BT codebook construction. Simulation results show that the proposed BT based signal detection achieves about the same bit error rate (BER) performance as the ML detection while the detection complexity is significantly reduced.

Noncoherent Two-Way Relaying With Decode and Forward: Two Versus Three Phases

Noncoherent two- and three-phase two-way relaying (TWR) techniques are bandwidth efficient and entail no pilot symbol–related rate loss. However, noncoherent two-phase TWR (2P-TWR) has not been compared with three-phase TWR (3P-TWR), and several unanswered questions remain. In this paper, we focus on the noncoherent detection of the relay with the decode-and-forward technique. For the noncoherent maximum-likelihood detector at the relay, we propose a distance measure for the transmitted signals of the two terminal nodes. For 2P-TWR, we propose that the signal constellation of one terminal node is the signal constellation of the other terminal node rotated by an angle. Using the proposed distance measure, we obtain the optimal angles and thus resolve those unanswered questions pertaining to 2P-TWR. Finally, noncoherent 3P-TWR was found to significantly outperform noncoherent 2P-TWR in simulations and distance analyses.

Reconfigurable Intelligent Surface-Aided Quadrature Reflection Modulation for Simultaneous Passive Beamforming and Information Transfer

Reflection modulation based on reconfigurable intelligent surface (RIS) is considered to be a promising information transfer mechanism, which does not require any additional radio frequency chains. However, existing reflection modulation schemes consider manipulating the ON/OFF states of RIS elements, which may result in some power loss. In this paper, we propose a new scheme, called RIS-aided quadrature reflection modulation (RIS-QRM), for better utilizing the reflection power in RIS-aided downlink multiple-input single-output (MISO) wireless systems. To this end, RIS-QRM partitions the RIS elements into two subsets in order to reflected the incident signals towards two orthogonal directions by using passive beamforming and encodes its local data onto the two partitions. A closed-form expression for the unconditional pairwise error probability of RIS-QRM in Rician fading is derived assuming maximum-likelihood detection at the receiver. Moreover, a low-complexity detection method that decouples the joint search of the constellation symbol and the RIS element partition is proposed. Computer simulation results corroborate the effectiveness of RIS-QRM and validate the analytical results. It is shown that RIS-QRM improves the error performance of the additional bits delivered by the RIS without deteriorating the error performance of the bits modulated on the constellation symbol, as compared to ON/OFF-based RIS-aided schemes.

Low-complexity soft ML detection for generalized spatial modulation

Generalized Spatial Modulation (GSM) is a recent Multiple-Input Multiple-Output (MIMO) scheme, which achieves high spectral and energy efficiencies. Specifically, soft-output detectors have a key role in achieving the highest coding gain when an error-correcting code (ECC) is used. Nowadays, soft-output Maximum Likelihood (ML) detection in MIMO-GSM systems leads to a computational complexity that is unfeasible for real applications; however, it is important to develop low-complexity decoding algorithms that provide a reasonable computational simulation time in order to make a performance benchmark available in MIMO-GSM systems. This paper presents three algorithms that achieve ML performance. In the first algorithm, different strategies are implemented, such as a preprocessing sorting step in order to avoid an exhaustive search. In addition, clipping of the extrinsic log-likelihood ratios (LLRs) can be incorporating to this algorithm to give a lower cost version. The other two proposed algorithms can only be used with clipping and the results show a significant saving in computational cost. Furthermore clipping allows a wide-trade-off between performance and complexity by only adjusting the clipping parameter.

Performance of signal detection with trellis code for downlink non-orthogonal multiple access visible light communication

This paper examines the implementation of multi-level amplitude modulation enforced by trellis coding in a downlink non-orthogonal multiple access channel for visible light communication (VLC). The non-orthogonal transmission is applied using superposition coding and successive interference cancellation with the support of a trellis decoder. The VLC is addressed by a channel model according to Lambert. Two levels of maximum likelihood signal detection are observed and compared, each for corresponding 4 and 8 trellis-coded modulation (TCM). The power ratio allotment is examined to investigate the system performance in the bit error rate. The simulation showed that a threshold of power ratio is needed to ensure good performance of signal detection. Further simulation with successive detection had shown effective results for up to three users.

Hybrid Multi Beamforming and Multi-User Detection Technique for MU MIMO System

Multi User—Multiple-input multiple-output based wireless communication system has several advantages over conventional MIMO systems such as high data rate and channel capacity which has drawn great attention recently and is prominently preferred for 5G systems. The other side interferences due to the Multi-User mobile environment such as co-channel interference and multiple access interference the overall system performance will be degraded. Highly reliable techniques need to be incorporated to improve the Quality of services. Moreover, the energy efficiency and compactness requirement of 5G systems present new challenges to investigate techniques for reliable communications. Introducing a novel low-complexity radix factorization based Fast Fourier transform multi beam former and maximal likelihood –multi-user detection techniques. As signal detector tailored with optimal sub-detector systems which results in considerable complexity reduction with intolerable error rate performance. The proposed radix factorized Fast Fourier transform—multi-beam forming architectures have the potential to reduce both hardware complexity and energy consumptions as compared to its state-of-the-art methods while meeting the throughput requirements of emerging 5G devices. Here through simulation results, the efficiency of the scaled ML sub-detector system at the downlink side is compared with the conventional ML detectors. Through experimental results, it is well proved that the proposed detector offers significant hardware and energy efficiency with the least possible error rate performance overhead.

Polarization Combining and Equalization in 5G Mobile-to-Mobile Systems

This article develops maximum likelihood (ML) detection for post-FFT processing of dual-polarized antenna outputs with a cyclic-prefix OFDM (CP-OFDM) waveform for a frequency selective multipath fading in a 5G mobile-to-mobile setting. The suggested maximum likelihood detector (MLD) comprises a combiner applied to the channel matched filter outputs (designated MLC) followed by a decision rule based on correlation and signal energy. When MLC is coupled with a frequency-domain equalizer, this structure is called MLC+FDE. The designed MLD and MLC+FDE are compared to the traditional combining techniques: maximum ratio combining, equal gain combining, and selection combining. Computer simulations performed over a stochastic channel model with polarization state information. The simulation results show that the difference between MLD and maximum ratio combining (the best performing method), MLC+FDE (almost the best performing method) and selection diversity with frequency-domain equalization (the worst performing method) is 2 dB. This diversity improvement is limited by the correlation between the two channels that characterize the two polarization states. This correlation makes it difficult to achieve reliable transmission through combining alone; some form of error control coding is also needed. When channel estimates are used in place of perfect channel knowledge, an error floor is observed.

Reconfigurable Intelligent Surface-Assisted Spatial Scattering Modulation

Reconfigurable intelligent surface (RIS) and spatial scattering modulation (SSM) are promising candidates for future generations of wireless communication. The former provides an enhanced transmission environment by providing an alternative communication path, while the latter boosts spectral efficiency. In this letter, we firstly propose a novel uplink millimeter-wave (mmWave) communication system that utilizes both RIS and SSM to support data transmission over wireless channels. Specifically, we design the reflecting phase shifters at the RIS to support the two-hop communications. Moreover, a maximum likelihood detector is adopted to a new system with RIS-SSM and a new analytical expression for a tight union upper bound on the bit error rate (BER) is derived. Monte Carlo simulation results are provided to verify the accuracy of the derived analytical expression. Numerical results reveal that the proposed RIS-SSM scheme has a significantly lower BER than the traditional SSM.

Neural Network-Based Fixed-Complexity Precoder Selection for Multiple Antenna Systems

In this paper, we propose a neural network-based precoder selection method for multiple antenna systems that are equipped with maximum likelihood detectors. We train a fully connected neural network by supervised learning with novel soft labels that are derived from the error probability of maximum likelihood detection. The dimension of the input data is reduced by QR decomposition of the channel matrices, thereby reducing the number of nodes of the input layer. Furthermore, the dimension reduction improves the network accuracy. The number of connections between the layers are reduced by the network pruning technique, then the survived connections are retrained to recover the degraded accuracy due to the pruning. We also optimize the regularization method, considering not only network overfitting but also pruning and retraining. Our method achieves a near optimal bit error performance of the previous sphere decoding (SD)-based symbolic algorithm, of which complexity fluctuates depending on channel matrices. Unlike the conventional SD-based method, the complexity of the proposed method is fixed by the intrinsic characteristic of neural network, which is desirable from the perspective of hardware implementation. And the fixed complexity is lowered by pruning unimportant connections of the networks. With the aid of computer simulations, we show that the fixed complexity of the proposed method is close to the average complexity of the conventional SD-based symbolic algorithm, allowing only negligible degradation of the error performance.

Amplify–Quantize–Forward Relay Channel With Quadrature Amplitude Modulation

This paper considers an amplify&#x2013;quantize&#x2013;forward (AQF) relay channel withM-ary quadrature amplitude modulation, where the relay implements amplification for the received signal and a uniform quantization for each of real and imaginary parts of the amplified version. Two step-size determinant methods for the uniform quantization affected by the power constraint at the relay are proposed by deriving the power and the mean square error for the quantized signal. Given the step size for the quantization, the maximum-likelihood detection is presented, and a linear combining detection called equivalent maximum ratio combining is proposed to reduce the detection complexity in the AQF relay channel. The simulation results confirm the superiority of the proposed quantization methods and detection algorithms.