Generalized Space Shift Keying Research Articles

RIS-Assisted Receive Generalized Space-Shift Keying and Receive Generalized Spatial Modulation

RIS-Assisted Receive Generalized Space-Shift Keying and Receive Generalized Spatial Modulation

OFDM-MIMO radar assisted dual-function radar communication system using index modulation

Dual-function radar communication (DFRC) system exploits a hardware platform to achieve both radar and communication functions. Compared to utilizing separate radar and communication systems, DFRC has better performance in spectrum utilization. In this paper, assisted by orthogonal frequency division multiplexing-multiple input multiple output (OFDM-MIMO) radar, we propose a DFRC system architecture combining generalized space shift keying (GSSK) modulation and subcarrier index modulation (SIM) techniques. In this scheme, linear frequency modulation (LFM) signal is explored as the transmission waveform of OFDM-MIMO radar to complete the radar function. Furthermore, the proposed scheme combines GSSK and SIM to carry the communication information to the antenna index and subcarrier index to complete the communication function. Based on this architecture, a novel low complexity frequency detection communication demodulation algorithm is proposed, and the achievable rate communication performance of the system is analyzed. Numerical and simulation results verify the feasibility and effectiveness of the proposed system.

Asymmetric Dual-Mode Constellation and Protograph LDPC Code Design for Generalized Spatial MPPM Systems

To achieve reliable and efficient transmissions in free-space optical (FSO) communication, this paper designs a new protograph low-density parity-check (PLDPC) coded generalized spatial multipulse position modulation (GSMPPM) system over weak turbulence channels. Specifically, we investigate the PLDPC code, generalized space shift keying (GSSK) modulation, and MPPM constellation. First, we propose a type of novel GSMPPM constellations that intelligently integrates the GSSK into MPPM, referred to as asymmetric dual-mode (ADM) constellations, so as to improve the performance of the PLDPC-coded GSMPPM system. Furthermore, exploiting a protograph extrinsic information transfer (PEXIT) algorithm, we construct a type of improved PLDPC code, referred to as I-PLDPC code, which outperforms the existing PLDPC codes over weak turbulence channels. Analytical and simulation results show that the proposed ADM constellations and the proposed I-PLDPC code can obtain noticeable performance gains over their counterparts. Therefore, the proposed PLDPC-coded GSMPPM system with ADM constellations is competent to satisfy the high-reliability requirement for FSO applications.

Received Antenna Array Design of GSSK-Based Antennas Selection for RIS-Assisted Communication

A wireless communication scheme named as the reconfigurable intelligent surface (RIS) assisted generalized space-shift keying (GSSK) based antennas selection (RIS-GKAS) is designed in this article. In this scheme, GSSK works at receiver and the reflected elements in the RIS can be adjusted to achieve the passive beamforming for the antennas selection to maximize the signal-to-noise ratio. This proposed scheme can be applied to a city with plenty of buildings. Specifically, the RIS is considered as an access point in this scheme and the received antennas are designed into a specific array for the antennas selection to achieve the passive beamforming. Besides, the performance analysis of the proposed scheme with maximum likelihood detector is presented. The results show that the RIS-GKAS has approving performance among various RIS-assisted index modulation schemes, and the designed pregreedy-aided maximum likelihood detector has the robustness among the multiple detectors under imperfect channel state information in RIS-GKAS scheme.

Machine learning assisted LEDs combination selection and user matching of RISs enabled GSSK-VLC system

To improve the performance of indoor generalized space shift keying (GSSK) visible light communication (VLC) system, multiple reconfigurable intelligent surfaces (RISs) enabled user matching and light emitting diodes (LEDs) combination selection approach is proposed. Firstly, the multiple RISs enabled GSSK-VLC system model is provided, which arranges multiple RISs to realize the full coverage of the service area in an indoor space. Then, based on received power, the special user is readily matched to the corresponding RIS. Finally, machine learning enabled LEDs combination selection techniques are exploited to reduce hardware costs and improve system bit error rate (BER) performance, wherein the machine learning approaches considered include k-nearest neighbor (k-NN), support vector machine (SVM), Naive Bayes (NB), and back propagation neural network (BPNN). Among these LEDs combination selection approaches, the BPNN has the best BER performance for the highest classification accuracy. Simulation results show that the proposed joint user-RIS matching and LEDs combination selection scheme can achieve better BER performance and reduce system complexity effectively.

Metasurface aided intelligent reflecting surfaces for indoor GSSK-VLC downlink

To provide high-quality communication in the indoor generalized space shift keying (GSSK) aided visible light communications (VLC) downlink transmission, especially when the line-of-sight (LoS) link is blocked, a metasurface aided intelligent reflecting surfaces (mIRS) scheme is proposed. By controlling the reflection characteristics of incident light in a deliberate manner provided in this paper, the proposed mIRS-assisted indoor GSSK-VLC downlink can significantly enhance the signal quality at the receiver end. Furthermore, the maximum likelihood (ML) and efficient preprocessing enabled sparsity orthogonal matching pursuit (OMP) detectors are respectively presented for the considered system. Finally, simulations are demonstrated to verify the effectiveness of the proposed mIRS-assisted indoor GSSK-VLC downlink transmission.

Naive Bayesian aided antenna selection for indoor NOMA GSSK VLC network

This paper investigates the light-emitting diodes (LEDs) combinations selection problem in indoor non-orthogonal multiple access (NOMA) enabled generalized space shift keying (GSSK) multi-user visible light communications (VLC) network. To address the high computational complexity in the optimal LEDs combination selection problem, a naive Bayes (NB) aided LEDs combination selection algorithm is proposed to alleviate the high complexity while guaranteeing the system performance. Firstly, the LEDs combination selection process is modeled as a multi-classification problem; Then, by setting the key performance indicator (KPI) as the maximal sum-rate of multiple users, the generated training samples set is utilized to train a classification model by the NB approach; Finally, the classification model is applied to the LEDs combination selection of new users. Simulation results demonstrate that, compared with the optimal LEDs combination selection algorithm, the NB aided selection scheme proposed in this paper can effectively reduce the computational complexity and achieve a better balance between algorithm complexity and network transmission performance.

Generalized Space Shift Keying for Ambient Backscatter Communication

We consider a generalized space shift keying (GSSK)-enabled multiple-input multiple-output (MIMO) ambient backscatter communication (ABC) system. We propose a scheme to exploit the multiple antenna structure of the system to achieve a lower error-rate performance than conventional ABC systems. Furthermore, we present a novel low complexity energy-based maximum likelihood (EML) GSSK detector, which does not require the perfect knowledge of the ambient source’s signal, unlike the conventional ABC receivers. To gain insights into the performance of the proposed scheme, we derive the exact pairwise error probability (PEP) of the EML detector and further obtain an upper bound on the probability of error. We also derive a simple asymptotic PEP expression as the number of antennas of the reader becomes large. Finally, we derive a simple, asymptotic PEP at the reader when the noise variance approaches zero, i.e., under the large signal-to-interference ratio regime. We validate our analysis through Monte Carlo simulations and show a small performance loss due to the approximations.

An IRS-Aided GSSK Scheme for Wireless Communication System

In this letter, we propose a novel communication scheme that combines intelligent reflecting surface (IRS) with generalized space shift keying (GSSK), where the IRS adjusts the phase shift according to the incoming bits at any specific time slot and multiple antennas are selected at the receiver to convey the index signals. Besides, a practical pre-greedy aided maximum likelihood (PGML) detector is proposed to supplement this IRS-aided received GSSK (IRS-RGSSK) system with lower complexity compared with the maximum likelihood (ML) detector and better error performance compared with the greedy detector (GD). By comparing with the IRS-aided received spatial modulation (IRS-RSM), the theoretical and simulation results show that the proposed system has better bit error rate (BER) performance.

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.

Deep Learning-Based Codebook Designs for Generalized Space Shift Keying Systems

In this paper, we propose a novel deep learning (DL)-based codebook design method for generalized space shift keying (GSSK) systems. In this DL-based method, the transmitter and receiver of GSSK systems are designed based on deep neural network (DNN). By training the DNN in an end-to-end manner, the DL-based method can adaptively generate suitable binary codewords and combine them into a codebook for GSSK systems. Simulation results show that the proposed DL-based method obtains better performance compared to conventional approaches.

Optimum GSSK Transmission in Massive MIMO Systems Using the Box-LASSO Decoder

We propose in this work to employ the Box-LASSO, a variation of the popular LASSO method, as a low-complexity decoder in a massive multiple-input multiple-output (MIMO) wireless communication system. The Box-LASSO is mainly useful for detecting simultaneously structured signals such as signals that are known to be sparse and bounded. One modulation technique that generates essentially sparse and bounded constellation points is the so-called generalized space-shift keying (GSSK) modulation. In this direction, we derive high dimensional sharp characterizations of various performance measures of the Box-LASSO such as the mean square error, probability of support recovery, and the element error rate, under independent and identically distributed (i.i.d.) Gaussian channels that are not perfectly known. In particular, the analytical characterizations can be used to demonstrate performance improvements of the Box-LASSO as compared to the widely used standard LASSO. Then, we can use these measures to optimally tune the involved hyper-parameters of Box-LASSO such as the regularization parameter. In addition, we derive optimum power allocation and training duration schemes in a training-based massive MIMO system. Monte Carlo simulations are used to validate these premises and to show the sharpness of the derived analytical results.

Sparsity Signal Detection for Indoor GSSK-VLC System

In this article, the signal detection problem in indoor visible light communication (VLC) system aided by generalized space shift keying (GSSK) is modeled as a sparse signal reconstruction problem, which has lower computational complexity by exploiting the sparse reconstruction algorithms in compressed sensing (CS). In order to satisfy the measurement matrix property to perform sparse signal reconstruction, a preprocessing approach of measurement matrix is proposed based on singular value decomposition (SVD), which theoretically guarantees the feasibility of utilizing CS based sparse signal detection method in indoor GSSK-VLC system. Then, by adopting classical orthogonal matching pursuit (OMP) algorithm and compressed sampling matching pursuit (CoSaMP) algorithm, the GSSK signals are efficiently detected in the considered indoor GSSK-VLC system. Furthermore, a more efficient detection algorithm combined with OMP and maximum likelihood (ML) is also presented especially for SSK scenario. Finally, the effectiveness of the proposed sparsity aided detection algorithms in indoor GSSK-VLC system are verified by computer simulations. The results show that the proposed algorithms can achieve better bit error rate (BER) and lower computation complexity than ML based detection method. Specifically, a signal-to-noise ratio (SNR) gain as high as 12 dB is observed in the SSK scenario and about 5 dB in case of a GSSK scenario upon employing our proposed detection methods.

Sum Rate Analysis of Generalized Space Shift Keying-Aided MIMO-NOMA Systems

We investigate the sum rate performance of a generalized space shift keying (GSSK)-aided, non-orthogonal multiple access (NOMA) network. In particular, we consider a multiple-input multiple-output (MIMO) NOMA downlink channel, where the base station employs GSSK modulation to transmit additional information to the NOMA users. We present a novel energy-based maximum likelihood (ML) detection strategy at the NOMA users to decode the active antenna indices. We derive a closed-form expression for the average pairwise error probability of the energy-based ML strategy to find a union bound on the bit error probability. Further, we derive the expression for the overall sum rate of the proposed GSSK-aided MIMO-NOMA system. Through numerical evaluations, we show that the proposed system outperforms the conventional MIMO-NOMA system, in terms of spectral efficiency.

Spatial Constellation Design-Based Generalized Space Shift Keying for Physical Layer Security of Multi-User MIMO Communication Systems

We propose a novel spatial constellation design (SCD) method with generalized space shift keying (GSSK-SCD) signaling for physical layer security (PLS) in multi-user (MU) multiple-input multiple-output (MIMO) communication systems. In GSSK-SCD, the received spatial constellations are optimized through a novel precoding scheme, which minimizes the BERs at legitimate users and significantly worsens eavesdroppers' BER. In addition to extensive BER simulations, we also provide analytical expressions for the secrecy rate regions for the proposed GSSK-SCD. Both analytical derivations and simulation results, including comparisons with artificial noise aided conventional GSSK, reveal that the GSSK-SCD approach provides significant PLS improvements for MU-MIMO systems.

Performance analysis and optimal detector of wireless optical space-time shift keying over the Gamma-Gamma turbulence channel.

In this paper, an optical space-time shift-keying (OSTSK) scheme based on the space-time dispersion matrix block of orthogonal design and laser selection technology is proposed to improve the transmission bits per symbol (TBS) and bit error rate (BER) performance of the traditional optical space shift keying (OSSK). The average BER of OSTSK is investigated over the Gamma-Gamma channel and simulated using the Monte Carlo method. The results show that the proposed scheme has the highest TBS and best BER performance compared with OSSK and optical generalized space shift keying. In addition, we propose a threshold judgment orthogonal matching pursuit (TJ-OMP)-decoding algorithm near-optimal detector for the OSTSK scheme to reduce the computational complexity of the system. For the OSTSK system with Nt=4 and Nr=4, when the reasonable threshold is selected as θ=1.5, the computational complexity of OSTSK-(TJ-OMP) is 74.3% lower than that of the OSTSK-maximum likelihood sequence detection (OSTSK-MLSD), while the signal-to-noise ratio of the OSTSK-(TJ-OMP) decreases by about 1.5 dB at BER=1×10-3.

Physical Layer Security for Multi-User MIMO Visible Light Communication Systems With Generalized Space Shift Keying

We consider the physical layer security (PLS) of multi-user (MU) multiple-input-multiple-output visible light communication (VLC) systems with an eavesdropper (Eve) and propose a novel spatial constellation design technique based on generalized space shift keying (MU-GSSK-SCD). The received signals of the legitimate users are optimized jointly, such that their bit error ratios (BERs) are minimized and Eve's BER is significantly degraded. The emission power of randomly selected light-emitting diodes is adjusted, by exploiting users' channel state information at the transmitter. Our strategy ensures that legitimate users receive confidential messages fully in an undistorted fashion, while any meaningful leakage to Eve is strongly prohibited, without any artificial noise addition. Every user can decode only its information, hence inter-user security is also guaranteed. The PLS improvements are presented in terms of both BERs and achievable secrecy rates in practical VLC scenarios. For various user configurations, it is shown that MU-GSSK-SCD increases the BER at Eve to the 0.5 level, while providing minimized BERs to the legitimate users. The achievable secrecy rate region is derived for MU-GSSK-SCD and it is shown that full secrecy can be achieved at 0 dB signal-to-noise ratio (SNR) level with a user separation as small as 90 cm.

Compressive Sensing-Based Low-Complexity Detector for GSSK-MIMO Systems

The generalized space shift keying (GSSK) technique proposed for massive MIMO systems has significant advantages in terms of hardware costs. However, the maximum likelihood (ML) detection for GSSK is computationally intractable. Consequently many suboptimal schemes with varying performance complexity trade-offs like compressive sensing (CS) detectors are proposed. Nevertheless, the existing CS detectors estimate the transmitted signal only by single-stage, which results in a decrease in detection performance. In order to solve this issue, we proposed a novel detection framework in this letter. Different from the existing CS detectors, the framework includes two stages: rough and precise selection. In the rough selection stage, the Euclidean distance criterion is employed instead of the traditional inner product operation to determine an optimized superset of active antenna indices. The precise selection stage performs a further traversal search over the superset acquired by the first stage to obtain the final indices. The simulation results illustrate that the performance of the proposed scheme can exhibit significant performance enhancement over the existing CS detectors while retaining the low complexity advantage.

Physical-Layer Security With Optical Generalized Space Shift Keying

Spatial modulation (SM) is a promising technique that reduces inter-channel interference while providing high power efficiency and detection simplicity. In order to ensure the secrecy of SM, precoding and friendly jamming are widely adopted in the literature. However, neither of those methods can take advantage of SM. In this paper, a novel spatial constellation design (SCD) technique is proposed to enhance the physical layer security (PLS) of optical generalized space shift keying (GSSK), which can retain some benefits of SM. Due to the lack of small-scale fading, the quasi-static characteristics of the optical channel is used to tailor the received signal at the legitimate user’s (Bob’s) side. The PLS of the system is guaranteed by the appropriate selection of the power allocation coefficients for randomly activated light emitting diodes (LEDs). With the aid of Bob’s channel state information at the transmitter, the bit error ratio (BER) of Bob is minimized while the BER performance of the potential eavesdroppers (Eves) is significantly degraded. Monte-Carlo simulation results show that the proposed SCD-zero forcing precoding (ZFP) forces Eve to experience a BER of around 0.5 by outperforming both the conventional and ZFP based GSSK for all practical signal-to-noise-ratio regimes and Bob-Eve separations.

Error rate performance analysis of power domain NOMA over AWGN and fading channels with generalized space shift keying in wireless 5G

The Non-Orthogonal Multiple Access (NOMA) emerged as a latest solution to demand of high data rated with excellent reliability and robustness. In this paper, the performance analysis of the NOMA under fading channel is presented with emphasis on error rate calculations. In addition, the focus is on exploring the impact of various modulation techniques like binary phase shift keying (BPSK), Quadrature Phase Shift Keying (QPSK) and Generalized Space Shift Keying (GSSK). The simulation study has been performed on MATLAB tool and results are analyzed efficiently in the metrics of NOMA.