Arbitrary Multiple-input Multiple-output Research Articles

Solving Doppler-Angle Ambiguity of BPSK-MIMO FMCW Radar System

In a multiple-input multiple-output (MIMO) radar system, binary phase-shift keying (BPSK) modulation is widely used to separate signals transmitted from multiple transmit (Tx) antennas. However, when the BPSK modulation is applied to the frequency-modulated continuous-wave (FMCW) radar system, there is an occurrence of Doppler-angle ambiguity due to the properties of the modulation scheme. In other words, the maximum detectable velocity is reduced in proportion to the number of Tx antennas, and the angle estimation performance can be degraded when a moving target induces a Doppler phase shift. Therefore, in this paper, we propose a method for solving the Doppler-angle ambiguity in the BPSK-MIMO FMCW radar system. The proposed method involves comparing and arranging the phases of signals corresponding to the same target in the range-velocity detection results. By arranging the phases to form an arithmetic sequence, the signals from each Tx antenna can be distinguished and the unambiguous velocity and angle of the target can be estimated. In addition, by using a general phase-shift keying (PSK) modulation scheme, the proposed method can be applied to an arbitrary MIMO system regardless of the number of Tx antennas.

Low-complexity MIMO demultiplexing scheme based on geometric vector extraction in visible light communication system

As one of the main optical wireless communication technologies, visible light communication (VLC) is considered a promising supplement in 5G/6G and the internet of things (IoT) networks. The multiple-input–multiple-output (MIMO) multiplexing scheme can significantly enhance a VLC system’s performance. To handle the blind MIMO demultiplexing, geometric vector extraction (GVE) algorithms are used in a mixture space (MS), which has not been presented in the extant literature. In a 2 × 2 VLC MIMO scenario, the singular value decomposition of an arbitrary MIMO channel matrix is introduced to discuss the one-to-one relationship between channel-matrix elements and the outline-shape conversion starting from the transmitted rectangular-shaped points in the MS. By extracting the vector features of the adjacent sides of the received parallelogram-shaped constellation points, we can obtain the elements of an unknown channel matrix and recover the superposed signals transmitted by two light-emitting diodes (LED). To obtain a vector from these constellation points, clustering is required to obtain the scattered points’ centroids in advance. To avoid falling into a local minimum, we present a clustering algorithm with an initial-position-expansion pre-processing stage to place the initial centroids with the greatest accumulated distance. To enhance the computational efficiency, we enhance the clustering algorithm via a single iteration to obtain the centroids, which we named the GVE-for-iteration-once (GVE–IO) algorithm. The enhanced algorithm has an equivalent or better MIMO demultiplexing performance and quick convergence performance compared to the fast independent component analysis (FastICA) algorithm. Moreover, the GVE–IO algorithm’s computational complexity and measured running time is reduced to 29% and 23%, respectively, of the FastICA algorithm’ time costs. Finally, the experimental investigation shows that the proposed scheme exhibits a significantly reduced computational complexity in all discussed voltage peak-to-peak (Vpp) cases of LED and a Q-value enhancement in two-thirds of the Vpp combination regions for 50 input points.

Near-Field Synthetic Spectrum Imaging Algorithm Based on Single-Frequency Sparse MIMO Array

This letter presents a two-dimensional near-field synthetic spectrum imaging algorithm based on a single-frequency sparse multiple-input–multiple-output (MIMO) array. By using an especially defined backward spreading function, the proposed algorithm migrates the scattered wave field under different illuminations. A synthetic spectrum can be obtained by synthesizing the spectrums of these migration results and then interpreted to the final reconstruction. The migration processing enables the algorithm to adapt to arbitrary apertures. Meanwhile, the influences of the limited aperture, the spreading loss, and the wavefront curvature in the near field are considered and compensated. High processing speed is achieved by using a large interpixel spacing during the migration processing and by the fast Fourier transform in the frequency-wavenumber (f-w) domain. Simulations and experiments are carried out, and the results demonstrate both the high-computational efficiency and the high flexibility for arbitrary sparse MIMO array apertures.

MIMO Underlay Cognitive Radio: Optimized Power Allocation, Effective Number of Transmit Antennas and Harvest-Transmit Tradeoff

In this paper, the performance of an underlay multiple-input multiple-output (MIMO) cognitive radio system is analytically studied. In particular, the secondary transmitter operates in a spatial multiplexing transmission mode, while a zero-forcing detector is employed at the secondary receiver. Additionally, the secondary system is interfered by single-antenna primary users (PUs). To enhance the performance of secondary transmission, optimal power allocation is performed at the secondary transmitter with a constraint on the maximum allowable outage threshold specified by the PUs. Further, the effective number of secondary transmit antennas is specified based on the optimal power allocation for an arbitrary MIMO scale. Also, a lower bound on the ergodic channel capacity of the secondary system is derived in a closed-form expression. Afterwards, the scenario of a massive MIMO secondary system is thoroughly analyzed and evaluated, where the harvesting-enabled secondary transmission is studied. The optimal power allocation, the effective number of secondary transmit antennas, the efficient tradeoff between transmit-and-harvest secondary antennas, and the average channel capacity of the secondary system are analytically presented. Finally, extensive numerical and simulation results corroborate the effectiveness of our analysis, while some useful engineering insights are provided.

Replication-Based Outer Bounds: On the Optimality of “Half the Cake” for Rank-Deficient MIMO Interference Networks

In order to gain new insights into multiple-input–multiple-output (MIMO) interference networks, the optimality of $\sum _{k=1}^{K} M_{k}/2$ (half the cake per user) degrees of freedom is explored for a $K$ -user MIMO interference channel where the cross-channels have arbitrary rank constraints, and the $k$ th transmitter and receiver are equipped with $M_{k}$ antennas each. The result consolidates and significantly generalizes results from prior studies by Krishnamurthy et al., of rank-deficient interference channels where all users have $M$ antennas; and by Tang et al., of full rank interference channels where the $k$ th user pair has $M_{k}$ antennas. The broader outcome of this paper is a novel class of replication-based outer bounds for arbitrary rank-constrained MIMO interference networks where replicas of existing users are added as auxiliary users and the network connectivity is chosen to ensure that any achievable scheme for the original network also works in the new network. The replicated network creates a new perspective of the problem, so that even simple arguments such as user cooperation become quite powerful when applied in the replicated network, giving rise to stronger outer bounds, than when applied directly in the original network. Remarkably, the replication-based bounds are broadly applicable not only to MIMO interference channels with arbitrary rank-constraints, but much more broadly, even beyond Gaussian settings.

Impact of Cochannel Interference on the Performance of Quadrature Spatial Modulation MIMO Systems

Quadrature spatial modulation (QSM) was proposed recently as a viable multiple-input multiple-output (MIMO) communication technique for future wireless systems. QSM expands spatial modulation to include both real and imaginary spatial constellation symbols. In this letter, we consider an arbitrary QSM MIMO system operating over Rayleigh fading channels and in the presence of additive white Gaussian noise and cochannel interference (CCI). The performance of the system is analyzed mathematically and numerically. In particular, a closed-form expression for the pairwise error probability is derived assuming arbitrary number of CCIs and used to calculate an upper bound on the average error probability. As well, an asymptotic expression, which is shown to be tight at practical SNR values is derived. Analytical results are sustained through Monte Carlo simulations and impact of different system parameters is studied. In addition, performance comparison between QSM, spatial modulation, spatial multiplexing, and single antenna transmission schemes for the same spectral efficiency and in the presence of CCI is presented.

On the Number of Interference Alignment Solutions for the $K$ -User MIMO Channel With Constant Coefficients

In this paper, we study the number of different interference alignment (IA) solutions in a $K$ -user multiple-input multiple-output (MIMO) interference channel, when the alignment is performed via beamforming and no symbol extensions are allowed. We focus on the case where the number of IA equations matches the number of variables. In this situation, the number of IA solutions is finite and constant for any channel realization out of a zero-measure set and, as we prove in this paper, it is given by an integral formula that can be numerically approximated using Monte Carlo integration methods. More precisely, the number of alignment solutions is the scaled average of the determinant of a certain Hermitian matrix related to the geometry of the problem. Interestingly, while the value of this determinant at an arbitrary point can be used to check the feasibility of the IA problem, its average (properly scaled) gives the number of solutions. For single-beam systems, the asymptotic growth rate of the number of solutions is analyzed and some connections with classical combinatorial problems are presented. Nonetheless, our results can be applied to arbitrary interference MIMO networks, with any number of users, antennas, and streams per user.

Maximum joint transmit-receive MRC gain with antennas exciting spherical vector wave modes up to order l

Derived is the maximum joint transmit and receive maximum ratio combining (MRC) diversity gain in arbitrary MIMO (multiple-input multiple-output) wireless propagation channels and the corresponding transmit and receive antenna coefficients. Also provided are numerical examples addressing two generic MIMO channel models based on the Kronecker correlation model with Laplacian angle-of-arrival (AoA) and angle-of-departure (AoD) distributions. In the analysis, spherical vector wave multipole modes of order l are considered, including both TE and TM modes.

Statistical Performance Analysis for MIMO Beamforming and STBC when Co-Channel Interferers Use Arbitrary MIMO Modes

In a cellular-like system, the multiple-input multiple-output (MIMO) mode used by a base station (BS) can be adaptively varied among several candidate MIMO modes, including space-time block coding (STBC), open-loop spatial multiplexing (OLSM), closed-loop spatial multiplexing (CLSM), MIMO beamforming (MBF), and maximal ratio transmission (MRT). In practice, during any one given period of time, when the desired BS performs downlink transmission with a specific MIMO mode, each co-channel interfering BS will use a MIMO mode the same as or different from that used in the desired link and any two co-channel interfering BSs may use different MIMO modes, so that the interference scenario becomes quite complicated. In this paper, considering realistic propagation conditions including both path-loss and Rayleigh fading and considering the existence of unequal-power interferers, the statistical distributions of the post-processing signal-to-interference ratios (SIRs) for either MBF or STBC downlink transmissions are analyzed when co-channel interfering BSs employ arbitrary MIMO modes. In particular, closed-form expressions for the probability density function (PDF) of the interference terms in the post-processing SIRs are derived. Further, the statistical distributions of the post-processing SIRs are analyzed. Simulation results verify the validity of the theoretical analyses.

The Error Probability of the Fixed-Complexity Sphere Decoder

The fixed-complexity sphere decoder (FSD) has been previously proposed for multiple-input multiple-output (MIMO) detection in order to overcome the two main drawbacks of the sphere decoder (SD), namely its variable complexity and its sequential structure. Although the FSD has shown remarkable quasi-maximum-likelihood (ML) performance and has resulted in a highly optimized real-time implementation, no analytical study of its performance existed for an arbitrary MIMO system. Herein, the error probability of the FSD is analyzed, proving that it achieves the same diversity as the maximum-likelihood detector (MLD) independent of the constellation used. In addition, it can also asymptotically yield ML performance in the high-signal-to-noise ratio (SNR) regime. Those two results, together with its fixed complexity, make the FSD a very promising algorithm for uncoded MIMO detection.

Filter Bank precoding for FIR equalization in high-rate MIMO communications

In this paper, the problem of designing finite-impulse-response (FIR) equalizers for multiple-input multiple-output (MIMO) FIR channels is considered. It is shown that an arbitrary MIMO frequency-selective channel can be rendered FIR equalizable by a suitable filter bank (FB) precoding operation that introduces redundancy at the transmitter. The expression for the minimum redundancy required to ensure FIR invertibility is derived. The analysis is extended to the case of MIMO multicarrier modulation. Optimum zero-forcing (ZF) and minimum mean-squared error (MMSE) solutions for the FIR equalizer are derived. Simulation results are provided to demonstrate that the proposed scheme achieves better performance than the block-processing methods while supporting a higher data rate.