This article proposes a two-fold triple system (TFTS)-based obfuscation scheme as a structured physical-layer transmission technique for multiple-input multiple-output (MIMO) systems. TFTS is a class of combinatorial block designs that enables index-based spatial signaling without cryptographic keys or additional computational overhead. The proposed scheme constructs a space-modulation matrix derived from a TFTS of orderv, where each row corresponds to a unique antenna activation pattern transmitting unmodulated carriers. The TFTS combinatorial space is generated by merging two non-isomorphic Steiner triple systems, yielding a mapping space that grows super-exponentially withv. This growth becomes extreme even for moderate dimensions; for example, atv= 40, the number of valid TFTS realizations exceeds 1010258, rendering exhaustive reconstruction computationally infeasible. The TFTS constellation matrix is assumed to be pre-shared and securely stored at the legitimate transceivers, while an eavesdropper is modeled as a fully informed and computationally unbounded adversary that lacks the correct TFTS mapping and therefore operates under mismatched decoding. Under this adversary model, Eve’s demodulation decisions degrade to random guesses, resulting in an average bit error rate (ABER) approaching 0.5 and negligible exploitable information. Accordingly, the proposed framework is explicitly positioned as a physical-layer obfuscation mechanism rather than a secrecy-capacity or cryptographic security scheme. The obfuscation strength of the system is evaluated through information-leakage analysis, quantifying the mutual information between transmitted indices and Eve’s observations, as well as detectability analysis based on hypothesis testing. Simulation results demonstrate that the proposed TFTS-obfuscation scheme preserves strong performance for the intended receiver in terms of ABER, mutual information, and achievable rate, while maintaining minimal information leakage and low detectability at the eavesdropper.

This paper addresses the implementation and performance analysis of sparse code multiple access (SCMA)-multiple-input multiple-output (MIMO) systems. SCMA is a promising technology to accommodate the ever-increasing number of users as well as spectral and bandwidth efficiency enhancements for next generations wireless systems. Also, MIMO techniques promise significant enhancements in reliability and spectral efficiency of wireless systems. In this study, spatial modulation (SM) and spatial multiplexing (SMX) MIMO techniques are considered along with SCMA. The analytical average bit error ratio (ABER) bound over Rayleigh fading channels is derived and shown to be accurate for a wide range of system parameters. Derived analytical formulas are corroborated through Monte Carlo simulation results and the impact of variant system and channel parameters on the performance of both SCMA-SMX and SCMA-SM systems are thoroughly investigated.

Capacity analysis of space modulation techniques (SMTs) multiple-input multiple-output (MIMO) systems were recently derived and significant enhancements were reported assuming perfect channel knowledge at the receiver. It was illustrated that SMTs achieve higher theoretical capacity than spatial multiplexing (SMX) MIMO system, which can be attained through designing signal symbols such that their distribution multiplied by the channel distribution leads to complex Gaussian distribution. Yet, perfect channel knowledge is impractical and channel estimation techniques must be considered, which cause channel estimation errors (CSE). Such errors are shown in previous literature to severely impact the performance of SMX MIMO system and prevent achieving the theoretical capacity of these systems. Therefore, the impact of CSE on the capacity of SMTs are studied in this paper. It is shown that Space modulation techniques (SMTs), and unlike SMX, can achieve the capacity in the presence of CSE and the conditions under which this can be obtained are derived over variant fading channels. Also, the impact of CSE on the overall capacity is discoursed. Validating the derived theoretical capacity formula through Monte Carlo simulation of the mutual information are presented over wide range of system and channel parameters.

Quadrature spatial modulation (QSM) is a recent multiple input multiple output transmission scheme that attracted significant research interest. QSM expands the spatial constellation diagram of spatial modulation (SM) to enhance the overall spectral efficiency while retaining all SM inherent advantages. In this paper, differential QSM (DQSM) is proposed to alleviate the requirement of channel knowledge at the receiver side. Receiver channel knowledge is crucial in QSM as part of the data are encoded in the Euclidean difference among different channel paths. Time dimension and orthogonal in-phase and quadrature spatial dimensions of QSM are exploited to facilitate differential modulation and demodulation while maintaining single RF-chain transmitters. In addition, a systematic design of the transmission blocks is provided for arbitrary number of transmit and receive antennas. Besides, a novel analytical framework for analyzing the performance of DQSM is derived and shown to predict accurate performance for differential SM and differential space shift keying systems as well. Analytical and simulation results are shown to match closely over a wide range of signal to noise ratios and for different system parameters.

Space modulation techniques (SMTs), in which some or all of the data bits modulate a block of spatial constellation symbol, are promising candidates for future 5G wireless systems. They promise data rate enhancements while maintaining low energy consumption, hardware cost, and computational complexity. As such, they attracted significant research interest in the past few years. One of the major assets of SMTs is the assumption that they can operate with a single RF chain at the transmitter even though multiple antennas might be activated at one time instant. Thus far, this claim is anticipated in several research articles but the transmitter designs of the different SMTs with a single RF chain are not addressed yet in the literature. SMTs include different system configurations, such as spatial modulation, space shift keying, quadrature spatial modulation, and quadrature space shift keying. The required hardware components to implement a transmitter for each of these systems with the minimum number of RF-chains are discussed in this paper. In addition, hardware limitations and the impact of different hardware blocks on the overall system performance are discussed. Besides, a comparison among different schemes along with conventional spatial multiplexing algorithm in terms of power consumption, hardware cost, probability of error, and receiver computational complexity is presented. It is shown that some of these techniques can operate without any RF-chain while a single-RF chain is sufficient for other systems. Moreover, these schemes can be traded off in terms of energy savings, complexity, performance, and cost.

Capacity analysis for millimeter-wave (mmWave) quadrature spatial modulation (QSM) multiple-input multiple-output (MIMO) system is presented in this paper. QSM is a new MIMO technique proposed to enhance the performance of conventional spatial modulation (SM) while retaining almost all its inherent advantages. Furthermore, mmWave utilizes a wide-bandwidth spectrum and is a very promising candidate for future wireless systems. Detailed and novel analysis of the mutual information and the achievable capacity for mmWave-QSM system using a 3-D statistical channel model for outdoor mmWave communications are presented in this paper. Monte Carlo simulation results are provided to corroborate derived formulas. Obtained results reveal that the 3-D mmWave channel model can be closely approximated by a log-normal fading channel. The conditions under which capacity can be achieved are derived and discussed. It is shown that the capacity of QSM system can be achieved, by carefully designing the constellation symbols for each specific channel model.

In this paper, for the first time real--world channel measurements are used to analyse the performance of spatial modulation (SM), where a full analysis of the average bit error rate performance (ABER) of SM using measured urban correlated and uncorrelated Rayleigh fading channels is provided. The channel measurements are taken from an outdoor urban multiple input multiple output (MIMO) measurement campaign. Moreover, ABER performance results using simulated Rayleigh fading channels are provided and compared with a derived analytical bound for the ABER of SM, and the ABER results for SM using the measured urban channels. The ABER results using the measured urban channels validate the derived analytical bound and the ABER results using the simulated channels. Finally, the ABER of SM is compared with the performance of spatial multiplexing (SMX) using the measured urban channels for small and large scale MIMO. It is shown that SM offers nearly the same or a slightly better performance than SMX for small scale MIMO. However, SM offers large reduction in ABER for large scale MIMO.

In this paper, Sphere Decoding (SD) algorithms for Spatial Modulation (SM) are developed to reduce the computational complexity of Maximum—Likelihood (ML) detectors. Two SDs specifically designed for SM are proposed and analysed in terms of Bit Error Ratio (BER) and computational complexity. Using Monte Carlo simulations and mathematical analysis, it is shown that by carefully choosing the initial radius the proposed sphere decoder algorithms offer the same BER as ML detection, with a significant reduction in the computational complexity. A tight closed form expression for the BER performance of SM—SD is derived in the paper, along with an algorithm for choosing the initial radius which provides near to optimum performance. Also, it is shown that none of the proposed SDs are always superior to the others, but the best SD to use depends on the target spectral efficiency. The computational complexity trade—off offered by the proposed solutions is studied via analysis and simulation, and is shown to validate our findings. Finally, the performance of SM—SDs are compared to Spatial Multiplexing (SMX) applying ML decoder and applying SD. It is shown that for the same spectral efficiency, SM—SD offers up to 84% reduction in complexity compared to SMX—SD, with up to 1 dB better BER performance than SMX—ML decoder.

In this paper, Sphere Decoding (SD) algorithms for Spatial Modulation (SM) are developed to reduce the computational complexity of Maximum--Likelihood (ML--) optimum detectors, which foresee an exhaustive search of the whole search space and have a complexity that linearly increases with the product of number of transmit--antenna, receive--antenna, and size of the modulation scheme. Three SDs specifically designed for SM are proposed and analyzed in terms of Bit Error Probability (BEP) and computational complexity. By judiciously choosing some key parameters, e.g., the radius of the sphere centered around the received signal, it is shown that the proposed algorithms offer the same BEP as ML--optimum detection, with a significant reduction of the computational complexity. Also, it is shown that none of the proposed SDs is always superior to the others, but the best SD to use depends on the system setup, i.e., the number of transmit--antenna, receive--antenna, and the size of the modulation scheme. The computational complexity trade--off offered by the proposed solutions is studied via analysis and simulation, and numerical results are shown to validate our findings.

In this paper a novel detection algorithm for spatial modulation (SM) based on sphere decoder (SD) tree search idea is proposed. The aim is to reduce the receiver complexity of the existing optimal decoder while maintaining an optimum performance. The algorithm performs a maximum likelihood (ML) search, only over those points that lie inside a sphere, centered at the received signal, of given radius. It is shown with the aid of analytical derivations, that for a SNR (signal-to-noise ratio) between 2~dB and 18~dB at least 45% and up to 85% reduction in the number of complex operations can be achieved with a close to optimal bit-error-ratio (BER) performance.