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Cloud-based cell-free massive multiple-input multiple-output (CFmMIMO) technology, which exploits a large number of distributed antennas to cooperatively serve multiple users, constitutes an appealing technique for B5G/6G wireless communications. However, the distributed nature of cloud-based CFmMIMO imposes great challenges in analyzing the error probability bounds, and very few efforts have so far been paid to optimize the detector design. In this paper, we try to add a stroke to this blank by analyzing the symbol error rate (SER) and design near-optimal detection algorithms. Specifically, considering non-identical large-scale coefficients and channel estimation errors, we first leverage the pairwise error probability to derive an asymptotic SER bound for uplink cloud-based CFmMIMO systems, which is verified by simulation results. Furthermore, motivated by the concepts of successive interference cancellation (SIC) and error correction mechanism (ECM), we design two distinct types of near-optimal detectors for cloud-based CFmMIMO systems and analyze their complexity and convergence performance. Finally, extensive simulation results show that our proposed SIC and ECM based detectors outperform conventional matched filtering (MF) and minimum mean squred error (MMSE) counterparts. In particular, the MMSE-SIC and MMSE-ECM detectors approach the derived asymptotic bound, and the MF-ECM detector strikes a balance between the SER and complexity in ultra CFmMIMO scenarios.

In this paper, a novel differential space-time block coded spatial modulation (differential STBC-SM) is proposed for uplink multi-user massive multiple-input multiple-output (MIMO) communications, which combines the concept of differential coding and STBC-SM to enhance the diversity benefits in the absence of the channel state information (CSI). The transmission structure of the proposed system is on a block basis, where each block contains two sub-blocks. More specifically, the first sub-block only conveys amplitude and phase modulation (APM) symbol bits, since its transmit antennas (TAs) obey a pre-designed activation pattern, which do not carry any information bit. For the second sub-block, the input bits are modulated to STBC-SM matrices, which are then differentially coded between two adjacent sub-blocks. Moreover, a novel block-by-block based non-coherent detector is presented. Finally, we derive an upper bound on the average bit error probability (ABEP) by using the moment generating function (MGF). Our simulation results show that the proposed differential STBC-SM transmission structure is able to acquire considerable bit error rate (BER) performance improvements compared to both the conventional differential spatial modulation (DSM) and differential Alamouti schemes.

This paper proposes a joint iterative optimization based hybrid beamforming technique for massive MU-MIMO systems. The proposed technique jointly and iteratively optimizes the transmitter precoders and combiners, aiming to approach the global optimum solution for the system sum-rate maximization problem. The proposed technique develops an adaptive algorithm exploiting the stochastic gradients (SG) of the local beamformers and provides low-complexity closed-form solutions. Furthermore, an efficient adaptive scheme is developed based on the proposed adaptive algorithm and the closed-form solutions. The proposed algorithm requires the signal-to-interference-plus-noise ratio (SINR) feedback from each user and a limited size transition vector to be exchanged between the transmitter and receivers at each step to update beamformers locally. Analytic result shows that the proposed adaptive algorithm achieves low-complexity when the array size is large and is able to converge within a small number of iterations. Simulation result shows that the proposed technique is able to achieve superior performance comparing to the existing state-of-art techniques. In addition, the knowledge of instantaneous channel state information (CSI) is not required as the channels are also adaptively estimated with each coherence time which is a practical assumption since the CSI is usually unavailable or have time-varying nature in real-time applications.

In this paper, an efficient compressive sensing detector is proposed for uplink grant-free non-orthogonal multiple access (NOMA), where the indices and symbols of the active users are detected separately by using efficient matching pursuit (MP) based algorithms. Specifically, a low-complexity subspace MP (SMP) algorithm is designed for detecting the active user's indices, which is helpful for obtaining an initial estimated symbol vector. Then an efficient MP based symbol correcting mechanism (SCM) is designed for finding and correcting the erroneous results encountered in the initial result. Simulation results indicate that our proposed SMP based SCM (SMP-SCM) algorithm is capable of exhibiting better bit error rate (BER) performance over the oracle least squares (OLS) counterpart in the high SNR regime, which is always taken as a benchmark in conventional multi-user detection of grant-free NOMA system.

Non-orthogonal Multiple Access (NOMA) has been envisioned as one of the key enabling techniques to fulfill the requirements of future wireless networks. The primary benefit of NOMA is higher spectrum efficiency compared to Orthogonal Multiple Access (OMA). This paper presents an error rate comparison of two distinct NOMA schemes, i.e., power domain NOMA (PD-NOMA) and Sparse Code Multiple Access (SCMA). In a typical PD-NOMA system, successive interference cancellation (SIC) is utilized at the receiver, which however may lead to error propagation. In comparison, message passing decoding is employed in SCMA. To attain the best error rate performance of PD-NOMA, we optimize the power allocation with the aid of pairwise error probability and then carry out the decoding using generalized sphere decoder (GSD). Our extensive simulation results show that SCMA system with “ $5\times 10$ ” setting (i.e., ten users communicate over five subcarriers, each active over two subcarriers) achieves better uncoded BER and coded BER performance than both typical “ $1\times 2$ ” and “ $2\times 4$ ” PD-NOMA systems in uplink Rayleigh fading channel. Finally, the impacts of channel estimation error on SCMA, SIC and GSD based PD-NOMA and the complexity of multiuser detection schemes are also discussed.

In this paper, we propose a differential multiple-input multiple-output (MIMO) scheme based on the novel concept of chaos-based time-varying unitary matrices to demonstrate—for the first time in the literature—the ability of differential encoding in achieving practical physical layer security even without the need for using channel estimation. In the proposed scheme, an erroneous secret key, which is extracted from the wireless nature, is used to initialize a chaos sequence that is responsible for generating artificially time-varying unitary matrices capable of obfuscating the transmitted data symbols from illegitimate eavesdroppers. Contrary to conventional studies, the key agreement ratio in this study is assumed to be imperfect, which is often true and very realistic in high-mobility scenarios. Following this, we conceive a new calibration algorithm for reconciling the chaotic sequence generated at the legitimate parties, thus making this calibration algorithm a unique, novel solution to the key sharing problem of conventional chaos-based communication techniques, which has been overlooked over the past few decades. It is found out that differential encoding obviates additional complexity and insecurity in dealing with channel estimation, whereas an eavesdropper must tackle the complicated differentially encoded patterns, which have an exponentially increasing complexity order. In addition, the obtained simulation results demonstrate that the proposed scheme can outperform conventional chaos-based MIMO schemes that assume perfect channel knowledge.

Orthogonal frequency division multiplexing (OFDM) with index modulation (IM) (OFDM-IM), which employs the activated sub-carrier indices to convey information, exhibits higher energy efficiency and lower peak-to-average power ratio (PAPR) than conventional OFDM systems. To further improve the throughput of discrete Fourier transform (DFT) based OFDM-IM (DFT-OFDM-IM), discrete cosine transform (DCT) based OFDM-IM (DCT-OFDM-IM) can be employed with double subcarriers given the same bandwidth. However, one of the main disadvantage of DCT-OFDM-IM is its lack of circular convolutional property over a dispersive channel. To address this issue, an enhanced DCT-OFDM-IM (EDCT-OFDM-IM) system has been proposed by introducing symmetric prefix and suffix at the transmitter and a pre-filter at the receiver leading to better performance than DFT-OFDM-IM in terms of bit error rate (BER). However, due to its special structure, it is difficult to derive the accurate average bit error probability (ABEP) upper bound, which is essential for the performance evaluation. In this paper, a tight ABEP upper bound is derived using the moment-generating-function (MGF). Our theoretical analysis is validated by simulation results and proven to be very accurate. Consequently the advantages of the EDCT-OFDM-IM system over the classic OFDM-IM system are further demonstrated analytically.

In this paper, a novel scheme dubbed space-time block coded rectangular differential spatial modulation (STBC-RDSM) is proposed for multiple-input and multiple-out (MIMO) systems, which combines space-time block coding (STBC) and rectangular differential spatial modulation (RDSM) to reap their respective benefits while avoiding the drawbacks of conventional differential spatial modulation (DSM) systems. More specifically, in the proposed STBC-RDSM scheme, information bits are conveyed via the rectangular differentially encoded antenna index matrices, as well as the STBC blocks. Furthermore, a low-complexity detection scheme is proposed. Our simulation results demonstrate that STBC-RDSM outperforms its conventional DSM counterparts in various spectral efficiencies. Finally, a closed-form union bound on the bit error rate (BER) is derived and validated by our simulation results.

A simplified rectangular differential spatial modulation (S-RDSM) scheme is conceived for massive multiple-input multiple-output (MIMO) systems dispensing with the channel state information (CSI). In the proposed S-RDSM scheme, the information bits are first mapped to a conventional SM symbol and then rectangular differential encoding is invoked between a pair of SM symbols. Then a non-coherent detector relying on a forgetting factor is developed, which requires no CSI at the receiver. Explicitly, a low-complexity hard limited maximum likelihood (HL-ML) detector is conceived for our generalized S-RDSM scheme, which is characterized by our theoretical analysis. Furthermore, we derive the optimal forgetting factor in closed form, which is capable of significantly reducing the complexity of the associated optimization. Finally, the upper bounds of the average bit error probability (ABEP) are derived using the moment generating function (MGF), and are validated by our simulation results. Both the theoretical and simulation results have shown that the proposed S-RDSM system outperforms the existing non-coherent schemes, despite operating at 10% of the benchmarker’s complexity, whilst approaching the performance of its coherent SM counterpart at a comparable complexity.

The concept of massive spatial modulation (SM) assisted vertical bell labs space-time (V-BLAST) (SM-VBLAST) system [1] is proposed, where SM symbols (instead of conventional constellation symbols) are mapped onto the VBLAST structure. We show that the proposed SM-VBLAST is a promising massive multiple input multiple output (MIMO) candidate owing to its high throughput and low number of radio frequency (RF) chains used at the transmitter. For the generalized massive SM-VBLAST systems, we first derive both the upper bounds of the average bit error probability (ABEP) and the lower bounds of the ergodic capacity. Then, we develop an efficient error correction mechanism (ECM) assisted compressive sensing (CS) detector whose performance tends to achieve that of the maximum likelihood (ML) detector. Our simulations indicate that the proposed ECM-CS detector is suitable both for massive SM-MIMO based point-to-point and for uplink communications at the cost of a slightly higher complexity than that of the compressive sampling matching pursuit (CoSaMP) based detector in the high SNR region.

Generalized index modulation (GIM) which implicitly conveys information by the activated indices is a promising technique for next-generation wireless networks. Due to the prohibitive challenge of bit-to-index combination (IC) mapping optimization, conventional GIM system obtains the bit-to-IC mapping table randomly, which may suffer from some performance loss. To circumvent this issue, we propose a low-complexity graph theory assisted bit-to-IC gray coding for GIM systems by minimizing the average hamming distance (HD) between any two ICs having one different value. Specifically, we decompose and transform the optimization problem into two subproblems using the graph theory, i.e., 1) Select an IC set whose corresponding graph has the minimum degree; 2) Design a bit-to-IC mapping principle to minimize the weight of the selected graph. Low-complexity algorithms are developed to solve the subproblems with a significant reduced complexity. Both simulation and theoretical results are shown that the GIM systems with our proposed mapping table are capable of providing significant performance gains over the conventional counterparts without the need for any additional feedback-link and without extra computational complexity. It is also shown that the proposed bit-to-IC mapping table is straightforward for any GIM systems over generalized fading channels.

A novel Multiple-Input and Multiple-Output (MIMO) transmission scheme termed as Space-Time Block Coded Quadrature Spatial Modulation (STBC-QSM) is proposed. It amalgamates the concept of Quadrature Spatial Modulation (QSM) and Space-Time Block Coding (STBC) to exploit the diversity benefits of STBC relying on sparse Radio Frequency (RF) chains. In the proposed STBC-QSM scheme, the conventional constellation points of the STBC structure are replaced by the QSM symbols, hence the information bits are conveyed both by the antenna indices as well as by conventional STBC blocks. Furthermore, an efficient Bayesian Compressive Sensing (BCS) algorithm is developed for our proposed STBC-QSM system. Both our analytical and simulation results demonstrated that the proposed scheme is capable of providing considerable performance gains over the existing schemes. Moreover, the proposed BCS detector is capable of approaching the Maximum Likelihood (ML) detector’s performance despite only imposing a complexity near similar to that of the Minimum Mean Square Error (MMSE) detector in the high Signal toNoise Ratio (SNR) regions.

In this paper, a novel multiple-input multiple-output (MIMO) transmission scheme termed space-time block coded differential spatial modulation (STBC-DSM) is proposed. It employs the hybrid concept of differential spatial modulation (DSM) and space-time block coding (STBC) to exploit the diversity benefits of STBC without the channel state information (CSI). In the STBC-DSM scheme, information bits are conveyed via the antenna matrix (AM) indices, as well as STBC blocks. Specifically, a novel AM set is first designed such that the transmitter requires only sparse (one or two) frequency radio (RF) chains. Then, the proposed STBC-DSM scheme is extended to the large-scale MIMO scenarios, and a low-complexity near-optimal detection algorithm is developed. Finally, an upper bound for the average bit error probability of the proposed scheme is derived. Both analytical and simulation results have shown that the proposed scheme is capable of achieving considerable performance gains over the existing DSM and differential Alamouti schemes.

An index modulation (IM) assisted Discrete Cosine Transform based Orthogonal Frequency Division Multiplexing (DCT-OFDM) with Enhanced Transmitter Design (termed as EDCT-OFDM-IM) is proposed. It amalgamates the concept of Discrete Cosine Transform assisted Orthogonal Frequency Division Multiplexing (DCT-OFDM) and Index Modulation (IM) to exploit the design freedom provided by the double number of available subcarrier under the same bandwidth. In the proposed EDCT-OFDM-IM scheme, the maximum likelihood (ML) detector used for symbol bits and index bits recovering is derived and the sophisticated designing guidelines for EDCT-OFDM-IM are provided. Based on the derived pairwise error event probability, a theoretical upper bound on the average bit-error probability (ABEP) of EDCT-OFDM-IM is provided over multipath fading channels. Furthermore, the maximum peak-to-average power ratio (PAPR) of our proposed EDCT-OFDM-IM scheme is derived and compared to than the general Discrete Fourier Transform (DFT) based OFDM-IM counterpart.

Discrete cosine transform (DCT) based orthogonal\ud frequency division multiplexing (OFDM), which has double number\ud of subcarrier compared to the classic discrete fourier transform\ud (DFT) based OFDM (DFT-OFDM) at the same bandwidth,\ud is a promising high spectral efficiency multicarrier techniques\ud for future wireless communication. In this paper, an enhanced\ud DCT-OFDM with index modulation (IM) (EDCT-OFDM-IM) is\ud proposed to further exploit the benefits of the DCT-OFDM and\ud IM techniques. To be more specific, a pre-filtering method based\ud DCT-OFDM-IM transmitter is first designed and the non-linear\ud maximum likelihood (ML) is developed for our EDCT-OFDM-IM\ud system. Moreover, the average bit error probability (ABEP) of the\ud proposed EDCT-OFDM-IM system is derived, which is confirmed\ud by our simulation results. Both simulation and theoretical results\ud are shown that the proposed EDCT-OFDM-IM system exhibits\ud better bit error rate (BER) performance over the conventional\ud DFT-OFDM-IM and DCT-OFDM-IM counterparts.

In this paper, Generalized Space-Time Block Coded Spatial Modulation (GSTBC-SM) is proposed for Multiple-Input and Multiple-Output (MIMO) system, which can be extended into an arbitrary even number of Transmit Antennas (TAs). The proposed GSTBC-SM scheme employs the hybrid concepts of Generalized Space-Time Block Coding (GSTBC) and Spatial Modulation (SM) to further exploit the diversity benefits of GSTBC using sparse Radio Frequency (RF) chains. To be more specific, the information bits are divided into Nu groups and each group is modulated by SM scheme. Finally, the Nu symbols are invoked for GSTBC structure. In order to demonstrated the advantages of our proposed GSTBCSM schemes, the theoretical Average Bit Error Probability (ABEP) of our proposed GSTBC-SM is derived. Both our analytical and simulation results demonstrated that the proposed GSTBC-SM scheme is capable of providing considerable performance gains over the corresponding GSTBC schemes at the same transmit rate associated with the same number of RF chains.

In this letter, a novel low-complexity detector based on the concept of compressive sensing (CS) is proposed for a novel multiple-input multiple-output system, namely, quadrature spatial modulation (QSM). In particular, the CS algorithm is performed in the real-valued system model, and the activated antenna indices, which are used to transmit the real and imaginary parts of QSM symbols, can be estimated separately. In order to further improve the performance of QSM, a novel search strategy is proposed. Simulation results show that the proposed detector is capable of achieving a considerable reduction in complexity compared with the maximum likelihood counterpart with negligible performance loss.

Generalized spatial modulation (GSM) is a recently proposed appealing multi-input multi-output (MIMO) transmission technique, which is capable of striking a tradeoff between the achievable transmission rate and the cost of radio frequency (RF) chains. In this letter, a novel low-complexity near-optimal soft decision (SoD)-aided detector is proposed for GSM, which considerably reduces the search space by employing a block minimum mean-squared error (B-MMSE) algorithm. Our simulation results show that the proposed detector is capable of achieving a better tradeoff between bit-error-rate (BER) performance and computational complexity compared with the existing matched filter (MF)-based SoD algorithms.

In this paper, a novel space-time block coded rectangular differential spatial modulation (STBC-RDSM) is proposed for multiple-input and multiple-out (MIMO) system, which combines the space-time block coding (STBC) and rectangular differential spatial modulation (RDSM) to take the advantages of RDSM and STBC systems, while avoiding the drawbacks of conventional differential spatial modulation (DSM) systems. More specifically, in the proposed STBC-RDSM scheme, the information bits are conveyed via the rectangular differential encoded antenna indices matrices, as well as the STBC blocks. Our simulation results demonstrate that STBC-RDSM outperforms the existing DSM systems for various spectral efficiencies.

Differential spatial modulation (DSM), which does not require the channel state information at the receiver, is an attractive alternative to its coherent counterpart. The optimal maximum-likelihood (ML) detector of the DSM system employs the classic block-by-block method for jointly detecting the activated antenna matrix (AM) and the modulation symbols, resulting in high computational complexity. In this letter, a low-complexity near-ML detector, which operates on a symbol-by-symbol basis, is proposed for the DSM scheme. Specifically, in each block, the index of the activated transmit antenna and modulation symbol in each time slot are first obtained, and then, these antenna indices are utilized to simply determine the index of the activated AM. Simulation results show that the proposed algorithm is capable of offering almost the same performance as that of the ML detector with more than 90% reduction in complexity.

Differential spatial modulation (DSM) is a novel attractive alternative technique for coherent spatial modulation (CSM) without channel state information (CSI) at the receiver. In this paper, iterative detection is firstly employed to improve the performance of DSM schemes. With the Hamming distance of two matrices reduced to the sum of simple elements, a lowcomplexity iterative detection scheme for recursive systematic convolutional (RSC) coded DSM scheme is proposed. Simulation results show that the proposed detector is capable of approaching a near- capacity performance with a great complexity reduction compared to the maximum a posteriori (MAP) detector.

In this paper, we design the low-complexity tree search-based detectors for generalized spatial modulation (GSM) aided single carrier (SC) systems over dispersive channels. Specifically, we commence with a brief review of the existing detection algorithms and then extend the sphere decoding-aided (SD) tree search algorithms designed for flat fading channels to GSM-aided SC systems. Moreover, a pair of reduced-complexity tree search algorithms are proposed by employing a hybrid concept of SD and M-algorithm to balance a tradeoff between the performance and complexity. Our proposed detectors are capable of recovering the transmit signal for both the overdetermine and underdetermine antenna configurations. Simulation results show that: 1) the extended SD-aided tree search algorithms are capable of providing the same performance as the maximum likelihood (ML) algorithm with reduced complexity; 2) the proposed novel algorithms exhibit lower complexity with negligible performance loss, compared with other tree search algorithms.