Spatial Modulation for Joint Radar-Communications Systems: Design, Analysis, and Hardware Prototype

In this paper, for the sake of enhancing the security of wireless transmission, we proposed a novel system based on spatial and direction modulation (SDM) combined with generalized spatial modulation (GSM) which is aided by covert information mapping (CIM), termed as the CIM-GSDM system. In such a system, the legitimated user is equipped with distributed receivers so as to demodulate the conveyed signal by exploiting its indices while disturbing eavesdroppers for information security. More specifically, part of the information is modulated into the indices of the legitimated distributed receiver subsets with the aid of the mapped covert information and the interference matrix, while another part of the message is arranged by conventional amplitude-phase modulation. The proposed system can reap the benefits from both GSM and CIM to make eavesdropper suffer great mixture. Furthermore, the detection scheme and theoretical analysis of error performance are discussed as well. The simulation results exhibit that the bit error rate (BER) performance of legitimate user is much better than that of the eavesdropper while the proposed scheme improves the security compared to the original CIM-SDM system at the same spectral efficiency.

We consider a multiple-input multiple-output (MIMO) dual function radar communication (DFRC) system employing frequency hopping (FH) radar waveforms. The DFRC system embeds communication symbols using code-shift keying (CSK) strategy. Each symbol is represented by a phase modulated pulse code sequence which multiplies the radar hops in fast-time before transmitted from the MIMO radar platform. This strategy allows for reduced clutter modulation caused by changed radar waveforms within coherent processing interval (CPI). We analyze the effect of this communication symbol embedding scheme on range sildelobe levels (RSLs) and derive the DFRC probability of target detection. We show that the DFRC waveforms enhances target visibility leading to improved target detection compared with the FH radar without signal embedding.

An adaptive physical-layer security enhancement framework for ambient backscatter communication in industrial IoT

Massive multiple‐input multiple‐output (MIMO) systems with hundreds of correlated antennas at base station are capable of offering abundant spatial resources. When spatial‐domain modulation is applied to these systems, the spatial modulation (SM) using only one radiofrequency chain benefits practical implementation, but suffers from significantly reduced multiplexing gain offered by the massive number of antennas. By contrast, the generalised SM (GSM) allows to simultaneously activate multiple transmit antennas, which improves spatial multiplexing gain, but degrades the achievable error performance, as its design pays no attention to the antenna correlation. The authors propose an antenna grouped SM (GrSM) scheme, which is capable of circumventing the shortcomings of both the SM and GSM schemes suffered in massive MIMO scenarios. In the proposed GrSM scheme, transmit antennas are partitioned into multiple groups, where the relatively strongly correlated antennas within individual groups are used to implement component SM schemes, while the relatively weakly correlated antennas in different groups are beneficial to obtain multiplexing gain. In order to further improve the spectral efficiency, adaptive modulation is integrated with GrSM to form the adaptive GrSM (AGrSM). The achievable error and spectral efficiency performance of GrSM and AGrSM systems are investigated based on both mathematical analysis and Monte‐Carlo simulations, which are also compared with that of the conventional SM and GSM schemes, when massive MIMO communication scenarios are considered. Their studies and performance results show that GrSM is a promising transmit scheme for massive MIMO, which can outperform both the SM and GSM schemes.

This paper explores the optimal number of antennas within generalized spatial modulation (GSM) scheme with single and multiple radio frequency (RF) chains. The main focus of our work is on the number of total transmit antennas and active transmit antennas as per the GSM transmission, that optimizes the system's power efficiency. Accordingly, the bandwidth efficiency of the transmission and receiver complexity are analytically calculated. The performance of the multiple-RF-chain GSM scheme is compared with SM and GSM. Moreover, Monte Carlo simulations are carried out to analyze and verify the analysis of power efficiency as a function of the number of transmit antennas.

For reducing the complexity of equalization, linear equalization can be adopted for generalized spatial modulation (GSM) which is a special case of multiple-input-and-multiple-output (MIMO). However, because of its inferior performance, linear equalization may be infeasible for practical GSM systems which has large number of antennas and constellation. On the other hand, lattice-reduction (LR) is an effective method to improve the performance of linear equalization. The lattice reduction can’t be utilized by GSM directly, because signals on some antennas don’t exist. For tackling this problem, we propose a compatible 8-QAM constellation scheme integrating LR-aided linear equalization with GSM effectively. Next, we prove that LR-aided linear equalizers collect the same diversity order as that exploited by the ML detector under Rayleigh fading channels, and implement some simulations. Simulation results show the superior of the proposed 8-QAM over traditional 4-QAM and 8-QAM under Rayleigh fading channel. Moreover, our scheme obtains the full receive diversity under correlated channel.

This paper considers the optimal constellation design for the generalized spatial modulation (GSM). The signal and spatial parts of the constellation are jointly designed where the signal part is not restricted to the conventional amplitude/phase modulation constellation points. The design problem is formulated as an optimization problem where a set of multi-dimensional constellation points that minimizes the average symbol error rate (SER) is selected. A gradient search algorithm is proposed to solve the optimization problem. Numerical results demonstrate the improved SER performance and increased energy efficiency of the proposed generalized signal- spatial constellation (GSSC) scheme as compared to previous spatial modulation (SM), GSM, and conventional MIMO schemes.

The idea of media-based modulation (MBM), introduced in [1] [2], is to embed information in the variations of the transmission media (channel states). This is in contrast to legacy wireless systems which embeds data in a radio frequency (RF) source prior to the transmit antenna. MBM offers several advantages over legacy systems, including “additivity of information over multiple receive antennas” and “inherent diversity over a static fading channel”. MBM is particularly suitable for transmitting high data rates using a single transmit unit and multiple receive antennas (single input multiple output MBM, or SIMO-MBM). Furthermore, layered multiple input multiple output MBM (LMIMO-MBM) [3] addresses hardware and decoding complexity along with training overhead when transmitting high data rates using a single MBM transmit unit. The current article compares the performance of MBM and LMIMO-MBM vs. legacy multiple input multiple output (MIMO) and emerging modulation techniques, spatial modu-lation (SM), and its variants, such as generalized SM (GSM) and quadrature SM (QSM). These comparisons demonstrate considerable performance gains for MBM and LMIMO-MBM vs. these notable schemes.

In multi-user multiple input multiple output (MIMO) systems, the non-orthogonal multiple access (NOMA) method based spatial modulation (SM) and generalized spatial modulation (GSM) can mitigate inter-user interference. However, the spectral efficiency of these methods is restricted because of antenna configuration. In this paper, a combination of the variable active antenna spatial modulation (VASM) scheme with the downlink power domain NOMA system, so-called NOMA-VASM, is proposed to improve spectral efficiency while main-taining mitigation of inter-user interference. In the novel NOMA-VASM, the antenna configuration is arbitrary and the number of enabled transmitting antennas (TAs) can be altered, so it is easier to increase spectral efficiency compared to NOMA-SM and NOMA-GSM. Monte Carlo simulations were performed under various scenarios, and the results showed that NOMA-VASM outperformed conventional NOMA-SM and NOMA-GSM in terms of spectral efficiency, average bit-error-rate (ABER) performance, and required number of TAs.

This paper investigates the generic signal shaping methods for the multiple-data-stream generalized spatial modulation (GenSM) and the generalized quadrature spatial modulation (GenQSM). Three cases with different channel state information at the transmitter (CSIT) are considered, including no CSIT, statistical CSIT, and perfect CSIT. A unified optimization problem is formulated to find the optimal transmit vector set under size, power, and sparsity constraints. We propose an optimization-based signal shaping (OBSS) approach by solving the formulated problem directly and a codebook-based signal shaping (CBSS) approach by finding the sub-optimal solutions in discrete space. In the OBSS approach, we reformulate the original problem to optimize the signal constellations used for each transmit antenna combination (TAC). Both the size and the entry of all signal constellations are optimized. Specifically, we suggest the use of a recursive design for the size optimization. The entry optimization is formulated as a non-convex large-scale quadratically constrained quadratic programming (QCQP) problem and can be solved by the existing optimization techniques with rather high complexity. To reduce the complexity, we propose the CBSS approach using a codebook generated by the quadrature amplitude modulation (QAM) symbols and a low-complexity selection algorithm to choose the optimal transmit vector set. The simulation results show that the OBSS approach exhibits the optimal performance in comparison with existing benchmarks. However, the OBSS approach is impractical for large-size signal shaping and adaptive signal shaping with instantaneous CSIT due to the demand of high computational complexity. As a low-complexity approach, the CBSS shows comparable performance and can be easily implemented in large-size systems.

Differential modulation schemes are very relevant in receivers having power and processing limitations, as these schemes dispense with the need for knowledge of channel coefficients for symbol detection. Spatial modulation (SM) is a scheme used in multi-antenna transmission scenarios where the data is transmitted in the amplitude, phase and spatial domains through selected antennas. In the coherent domain, generalized SM (GSM) employs multiple antennas in combination during every time slot to enhance the spectral efficiency (SE). In this paper, we propose two differential schemes which activate two or more antennas at a time to transmit the modulated symbol. These schemes achieve higher SE using a lesser number of antennas and lower order modulation schemes instead of the higher number of antennas required for conventional SM schemes based on differential modulation. Simulation studies reveal that the proposed schemes have better bit error rate performance than traditional differential SM schemes. We also derive the analytical union bound for the proposed schemes and is satisfied from medium to high signal-to-noise ratio (SNR) ranges.

Massive multiple input multiple output (MIMO), also known as a very large-scale MIMO, is an emerging technology in wireless communications that increases capacity compared to MIMO systems. The massive MIMO communication technique is currently forming a major part of ongoing research. The main issue for massive MIMO improvements depends on the number of transmitting antennas to increase the data rate and minimize bit error rate (BER). To enhance the data rate and BER, new coding and modulation techniques are required. In this paper, a generalized spatial modulation (GSM) with antenna grouping space time coding technique (STC) is proposed. The proposed GSM-STC technique is based on space time coding of two successive GSM-modulated data symbols on two subgroups of antennas to improve data rate and to minimize BER. Moreover, the proposed GSM-STC system can offer spatial diversity gains and can also increase the reliability of the wireless channel by providing replicas of the received signal. The simulation results show that GSM-STC achieves better performance compared to conventional GSM techniques in terms of data rate and BER, leading to good potential for massive MIMO by using subgroups of antennas.

Application of LFM-CPM signal into a DFRC system based on circulating code array

Link adaptation is crucial in the upcoming broadband wireless systems, where there are stringent Quality of Service (QoS) requirements. It is well established in single antenna systems, whereas it is challenging and at the same time promising in Multiple Input Multiple Output (MIMO) communication. Changing the modulation order/coding scheme or switching between MIMO modes for adaptation is rather complex and requires high adaptive control overhead. As an alternative, error control coding, which is widely used in MIMO can be modified to make the system rate adaptive, with or without constellation change. In this paper, we present an adaptive transmission technique in Generalised Spatial Modulation (GSM) MIMO using Rate Compatible Punctured Convolutional (RCPC) codes. An antenna grouping method based on limited channel state information (CSI) feedback is used here to select the puncturing matrices and the active antennas. The system throughput and BER performance are analyzed for various channel selection and puncturing schemes.

Generalized spatial modulation (GSM) extends the achievable capacity of spatial modulation, by selecting multiple antennas for transmissions instead of only one. Due to the sparse structure of GSM, it can help reduce the power of mutual interference in non-orthogonal multiple access (NOMA). However, GSM-NOMA imposes significantly high detection complexity as multiple different antenna transmission patterns are used to carry the information for frequency-sharing users. In this paper, we propose a GSM-NOMA detector that has high detection performance and low complexity, namely, the two-stage maximum likelihood (ML) detector. Simulation results validate the theoretical analysis and demonstrate that the proposed scheme always achieves lower bit error rate, while the computational complexity can be significantly reduced, compared to conventional successive interference cancellation detection.