Multiple-input Single-output Channel Research Articles

Performance Analysis of SIMO–OFDM Systems With Pilot-Aided Channel Estimation

Pilot symbols are commonly modulated on uniformly spaced subcarriers to aid channel estimation, thereby facilitating data demodulation in practical orthogonal frequency-division multiplexing (OFDM) systems operating over quasi-static multipath channels, where the channel frequency response (CFR) remains static within one block. Aided by uniformly spaced pilot symbols, the direct least-square CFR estimation can enable reliable symbol-by-symbol data demodulation within the same OFDM block, based on the principle of generalized likelihood ratio test (GLRT). Such GLRT-based OFDM can be easily incorporated with single-input multiple-output (SIMO) antenna technique to enhance data demodulation over quasi-static channels exhibiting random multipaths. In this article, an upper bound to the average bit error probability (BEP) is analytically derived for this GLRT-based SIMO–OFDM system over quasi-static random multipath channels. The analysis is generally applicable to arbitrary two-dimensional component modulations when the quasi-static SIMO channel consists of independent but not necessarily identically distributed random channel paths with Rician or Rayleigh distributed path response magnitudes. The BEP upper bound facilitates the error performance characterization of the GLRT-based SIMO–OFDM system with respect to data-to-noise power ratio, data-to-pilot power ratio, antenna diversity, pilot density, and pilot power allocation.

Localizing the Unknown Receiver in a Diffusive SIMO Molecular Communication System

This letter introduces a method to estimate the position of an unknown fully absorbing (FA) spherical receiver in a diffusive molecular communication (MC) system. This latter consists of a point transmitter and multiple FA spherical receivers in a three-dimensional space. The method relies on a temporal asymptotic single-input multiple-output (SIMO) channel model for diffusive MC systems that takes into account the interaction among receivers. By relying on the asymptotic model, a grid-based likelihood function is a priori created from each known receiver’s perspective. The likelihood function’s computation requires information about the number of molecules released by the transmitter, its position, and the position of known receivers. From the cumulative number of molecules absorbed by the known FA receivers, different likelihood maps are obtained, where each map corresponds to the likelihood of the position of unknown receiver from a specific known receiver’s perspective. By combining the receivers’ likelihood maps, which is equivalent to cooperation by sharing their knowledge, the position of the unknown receiver is estimated. The quality of the estimation is evaluated in terms of root mean squared error (RMSE) between the estimated position of the unknown receiver and its true position for different number of released molecules.

Signal-Power-Based Combination Weight Rule for Distributed Blind Equalization in WSN Model

In this paper, we consider how to improve the performance of distributed estimation over a diffusion network in order to estimate the unknown parameter of interest from noisy measurements. Specifically, the distributed blind equalization based on the single-input multiple-output channel model over a wireless sensor network (WSN) is discussed in this paper. We propose a new combination weight rule that the weight of each sensor node is assigned by the signal power of the sensor (received) signal instead of only the degree of each sensor node. We assume that each channel from the common transmitter to the sensor nodes in the WSN is common and that noises, the variances of which are different, are included at each channel. The average mean square error and symbol error rate performance characteristics of the distributed blind equalization are investigated. Simulations show that a significant performance improvement is obtained by employing the proposed combination weight rule compared with using conventional combination weight rules.

Intelligent Reconfigurable Surface-Aided Space-Time Line Code for 6G IoT Systems: A Low-Complexity Approach

Intelligent reconfigurable surfaces (IRS) have attracted much attention from both industry and academia due to their performance improving capability and low complexity for 6G wireless communication systems. In this letter, we introduce an IRS-assisted space-time line code (STLC) technique. The STLC was introduced as a promising technique to acquire the optimal diversity gain in 1×2 single-input multiple-output (SIMO) channel without channel state information at receiver (CSIR). Using the cosine similarity theorem, we propose a novel phase-steering technique for the proposed IRS-assisted STLC technique. We also mathematically characterize the proposed IRS-assisted STLC technique in terms of outage probability and bit-error rate (BER). Based on computer simulations, it is shown that the results of analysis shows well match with the computer simulation results for various communication scenarios.

FIR-SIMO channel order determination by invariant-signal-subspace matching

We present a novel and computationally simple solution to the problem of determining the order of finite impulse response (FIR) single-input multiple-output (SIMO) channel. The solution is applicable to ideal and realistic wireless channels, with both white and colored noise. It is based on a non-asymptotic goodness-of-fit metric, referred to as invariant-signal-subspace matching (ISSM), aimed at matching pairs of invariant-signal-subspaces, created by exploiting the shift-invariance property of the block-Toeplitz data matrix. A pair of projection matrices corresponding to these subspaces is created for every potential FIR-SIMO order, and the order is then determined as that for which this metric is minimized. Simulation results are included, demonstrating the performance of the proposed solution for both ideal and realistic channels, with both white and colored noise.

The Effect of Time Delay on the Average Data Rate and Performance in Networked Control Systems

This paper studies the performance of a feedback control loop closed via an error-free digital communication channel with transmission delay. The system comprises a discrete-time noisy linear time-invariant (LTI) plant whose single measurement output is mapped into its single control input by a causal, but otherwise arbitrary, coding and control scheme. We consider a single-input multiple-output (SIMO) channel between the encoder-controller and the decoder-controller which is lossless and imposes random time delay. We derive a lower bound on the minimum average feedback data rate that guarantees achieving a certain level of average quadratic performance over all possible realizations of the random delay. For the special case of a constant channel delay, we obtain an upper bound by proposing linear source-coding schemes that attain desired performance levels with rates that are at most 1.254 bits per sample greater than the lower bound. We supplement our results with a numerical experiment demonstrating that the obtained bounds and operational rates are increasing functions of the constant delay.

Energy detection investigation over composite [formula omitted]/inverse-gamma wireless channel

Proper utilization of the unused spectrum hole facilitates the expanding necessity of the elevated data rate in the upcoming 5th Generation (5G) wireless communication technology. Energy detection is a widely worked technique to fulfill this requirement with minimal time, cost, and efforts. With this motivation, this work develops an analytical framework to analyze the functioning of an energy detector (ED) based cognitive radio (CR) system over a composite fading distribution, characterized by α-μ/Inverse-Gamma (I-Gamma) composite fading channel. To begin with, closed-form expressions for the probability density function (PDF) are developed for single-input single-output (SISO) and single-input multiple-output (SIMO) channels. Exploiting these expressions, analytical results for the average probability of detection (PD) and the average area under the receiver operating characteristic curve (AUC) are obtained. Further, the breakdown is extended in determining average PD under high and very low signal-to-noise ratio (SNR) regime. Finally, the results are utilized as an application in analyzing the cooperative spectrum sensing (CSS) under different shadowing conditions. The optimization of the number of cognitive radios is carried out using the r-out-of-N voting rule. The validation of all the proposed results and their accuracy is determined using the Monte-Carlo simulations.

Generalized Degrees Freedom of Noncoherent MIMO Channels With Asymmetric Link Strengths

We study the generalized degrees of freedom (gDoF) of block-fading noncoherent multiple input multiple output (MIMO) channels with asymmetric distributions of link strengths and a coherence time of T symbol durations. We derive the optimal signaling structure for communication for the asymmetric MIMO channel, which is distinct from that for the MIMO channel with independent and identically distributed (i.i.d.) links. We extend the existing results for the single input multiple output (SIMO) channel with i.i.d. links to the asymmetric case, proving that selecting the statistically best antenna is gDoFoptimal. Using the gDoF result for the SIMO channel, we prove that for T = 1, the gDoF is zero for MIMO channels with arbitrary link strengths. We show that selecting the statistically best antenna is gDoF-optimal for the multiple input single output (MISO) channel. We also derive the gDoF for the 2 x 2 MIMO channel with different exponents in the direct and cross links. In this setting, we show that it is always necessary to use both the antennas to achieve the gDoF, in contrast to the results for the 2 x 2 MIMO channel with i.i.d. links. We show that having weaker crosslinks, gives gDoF gain compared to the case with i.i.d. links. For the noncoherent MIMO channel with i.i.d. links, the traditional method of training each transmit antenna independently is degrees of freedom (DoF) optimal, whereas we observe that for the asymmetric 2 x 2 MIMO channel, the traditional training is not gDoF-optimal. We extend this observation to a larger MxM MIMO channel by demonstrating a strategy that can achieve larger gDoF than a traditional trainingbased method.

Robust Secrecy Rate Optimizations for Healthy Monitoring System MISO Channel with D2D Communications

In this paper, we study the robust secrecy rate optimization of multiple-input-single-output (MISO) security channels with multiple device-to-device (D2D) communication in an electronic physical system for health monitoring applications. We focus on the problems of robust power minimization and maximizing robust secrecy with transmit power in this system. Both of these robust optimizations are subject to probability-based secrecy and D2D transmission rates. The design of robust beamforming can consider combining statistical channel uncertainty model (CUM), but the problem of construction is a non-convexity problem that is not easy to solve, so we propose two methods to solve this problem: based on Bernstein-type inequality and a conservative approximation of S-Procedure. The simulation results demonstrate that the performance of the S-Procedure method on the reachable confidentiality rate is not as good as the method based on the Bernstein-type inequality.

A 3D Non-Stationary GBSM for Vehicular Visible Light Communication MISO Channels

The potential of using visible light communication (VLC) technologies for vehicular communication networks has recently attracted much attention. The underlying VLC channels, as a foundation for the proper design and optimization of vehicular VLC communication systems, have not yet been sufficiently investigated. Vehicular VLC link impairments can have a significant impact on the system performance and capacity. Such impairments include the optical wireless channel distortion and background noise. This paper proposes a novel three-dimensional (3D) regular-shaped geometry-based stochastic model (RS-GBSM) for vehicular VLC multiple-input single-output (MISO) channels. The proposed 3D RS-GBSM combines a two-sphere model and an elliptic-cylinder model. Both the line-of-sight (LoS) and single-bounced (SB) components are considered. The proposed model jointly considers the azimuth and elevation angles by using von-Mises-Fisher (VMF) distribution. Based on the proposed model, the relationship between the communication range and the received optical power is analyzed and validated by simulations. The impact of the elevation angle in the 3D model on the received optical power is investigated by comparing with the received optical power of the corresponding two-dimensional (2D) model. Furthermore, the background noise is also modeled to evaluate the system's signal-to-noise ratio (SNR).

Fundamental Capacity Analysis for Identically Independently Distributed Nakagami-q Fading Wireless Communication

With the advancement in technology, decent trans-fer rate of data for fast communication is an exigency. Different distributions on different wireless communication channels have been used previously to model them and to do performance analysis on the systems. In this work, capacity analysis of iden-tically independently distributed Nakagami-q fading single-input multiple-output (SIMO) wireless communication is presented. The derivation of channel capacity with the analytical solution have been conducted using small limit argument approximation. Where the small limit argument approximation corresponds to the low signal-to-noise ratio (SNR) regime. SIMO channel capacity behavior with respect to number of receiver antennas and with respect to SNR have been explored in depth. The improvement of capacity is depicted rigorously. It has been found that using Nakagami-q distribution, capacity of the system increases as number of receiver antenna increases. It is also found that the capacity of this SIMO wireless system can be further improved through changing of certain parameters.

On the Capacity of MISO Channels With One-Bit ADCs and DACs

A one-bit wireless transceiver is a promising communication architecture that not only can facilitate the design of mmWave communication systems but also can extremely diminish power consumption. The non-linear distortion effects by one-bit quantization at the transceiver, however, change the fundamental limits of communication rates. In this paper, the capacity of a multiple-input single-output (MISO) fading channel with one-bit transceiver is characterized in a closed form when perfect channel state information (CSI) is available at both a transmitter and a receiver. One major finding is that the capacity achieving transmission strategy is to uniformly use four multi-dimensional constellation points. The four multi-dimensional constellation points are optimally chosen as a function of the channel and the signal-to-noise ratio (SNR) among the channel input set constructed by a spatial lattice modulation method. As a byproduct, it is shown that a few-bit CSI feedback suffices to achieve the capacity. For the case when CSI is not perfectly known to the receiver, practical channel training and CSI feedback methods are presented, which effectively exploit the derived capacity-achieving transmission strategy.

Sub-Band Versus Space-Delay Precoding for Wideband mmWave Channels

Precoding for frequency-selective multiple-input single output channels is often performed on a sub-band basis in frequency-domain. Such sub-band precoding will also be adopted in the upcoming 3GPP Release 15 New Radio. Exploiting the large available bandwidth at millimeter-Wave (mmWave) frequencies will significantly increase the number of sub-bands, and hence the feedback overhead when sub-band precoding is applied. In this letter, we propose a precoding scheme that exploits the sparsity of mmWave channels by performing precoding in the space-delay domain. It is shown that the proposed precoder outperforms the former in terms of average mutual information and reduces the feedback overhead.

Optimal Signaling Schemes and Capacities of Non-Coherent Correlated MISO Channels Under Per-Antenna Power Constraints

This paper investigates the optimal signaling schemes and capacities of non-coherent correlated multiple-input single-output (MISO) channels in fast Rayleigh fading. We consider both channels under per-antenna power constraints as well as channels under joint per-antenna and sum power constraints. For per-antenna power constraint channels, we first establish the convex and compact properties of the feasible sets, and demonstrate the existence of optimal input distribution and the uniqueness of optimal effective magnitude input distribution. By exploiting the solutions of a quadratic optimization problem, we show that the Kuhn–Tucker condition on the optimal inputs can be simplified to a single dimension. As a result, we can apply the Identity Theorem to show the discrete and finite nature of the optimal effective magnitude distribution, with a mass point located at the origin. By using this distribution, we then construct a finite and discrete optimal input vector distribution. The use of this input allows us to determine the capacity gain of MISO over SISO via the phase solutions of a constrained quadratic optimization problem on a sphere, which can be obtained using a proposed penalized optimization algorithm. We also extend the results to MISO channels subject to the joint per-antenna and sum power constraints. Under this consideration, it is shown that not all per-antenna constraints are active. While the finiteness and discreteness of the optimal effective magnitude and the optimal input vector distributions still hold, the optimal phases and the optimal power allocation among the transmit antennas need to be determined simultaneously via a quadratic optimization problem under inequality constraints. These solutions can finally be used to obtain the MISO capacity gain.

Space-Time Blind Equalization of Dispersive MIMO Systems Driven by QAM Signals

This paper investigates space-time blind equalization (BE) of dispersive multiple-input multiple-output communication systems driven by high throughput quadrature amplitude modulation signals. Multistage processing is adopted to overcome the severe local convergence problem in BE. First, a good initial value for the equalizer is obtained by forcing one of the system inputs with desired delay to be recovered. Then, the fast multimodulus algorithm (MMA) is used to roughly equalize the communication system. After that, an improved MMA (IMMA) is developed to effectively search for a fine equalizer for the system. Moreover, the novel modified Newton method (MNM) proposed in our previous work is employed to fast optimize the MMA and IMMA cost functions, which significantly reduces the computational load. Furthermore, the proposed algorithm has an additional benefit that once a signal is recovered, its corresponding single-input multiple-output channel impulse response is estimated by the classical least squares methods. Then, the influence of the recovered signal to the original received signals is removed to avoid extracting this recovered signal repeatedly. The quadratic rate of convergence of the MNM is theoretically analyzed, and the good equalization performance of the IMMA is explained. Finally, simulation results are provided to illustrate the effectiveness of the proposed algorithm.

MISO Channel Estimation and Tracking from Received Signal Strength Feedback

Downlink channel estimation is an important task in any wireless communication system, and 5G massive multiple-input multiple-output in particular—because the receiver must estimate and feed back to the transmitter a high-dimensional multiple-input single-output (MISO) vector channel for each receiving element. This is a serious burden in terms of mobile computation and power, as well as uplink communication overhead. The starting point of this paper is that all existing and emerging wireless communication systems provide basic Received Signal Strength (RSS) / Channel Quality Indicator (CQI) feedback to compensate for temporal channel variations. Is it possible to estimate and track the vector MISO channel from RSS/CQI feedback alone? This paper shows that the answer is affirmative, if one employs time-varying beamforming and phase modulation together with phase retrieval ideas from optics and crystallography. Three efficient algorithms that cover different model assumptions are proposed to track the vector MISO channel on the transmitter's side using only RSS/CQI feedback. Numerical simulation results under various settings validate the efficacy of the proposed algorithms in tracking a slowly time-varying vector MISO channel. Interestingly, this is the first application of phase retrieval where assuming independent and identically distributed Gaussian measurement vectors can be practically justified.

Secrecy Mutual Information of the Independent and Identically Distributed Nakagami-q Fading SIMO Channel

ABSTRACTIn this paper, we consider an independent and identically distributed Nakagami-fading single-input multiple-output (SIMO) channel, where the transmitter sends some confidential message to the legitimate receiver in the presence of an eavesdropper. Both the receiver and the eavesdropper have multiple antennas. We formulated the probability of non-zero secrecy mutual information, secure outage probability, and ergodic secrecy mutual information for the SIMO wireless communication system. The calculations have been carried out using small limit argument approximation on zeroth-order modified Bessel function of first kind. This approximation provides decent results in the low signal-to-noise-ratio (SNR) regime. In the low-SNR regime, either the transmission power is small or the bandwidth is large. In either case, it is difficult for an eavesdropper to detect the signals in this regime. We present that in the presence of fading, positive secrecy mutual information is achievable even when the eavesdropper has better SNR than the main channel. We also found in our work that at low-SNR regime, the effect of number of eavesdropper's channel on average secrecy mutual information is almost negligible.

Measurements and Analysis of Angular Characteristics and Spatial Correlation for High-Speed Railway Channels

Spatial characteristics of the propagation channel have a vital impact on the application of multi-antenna techniques. This paper analyzes angular characteristics and the spatial correlation for high-speed railway (HSR) channels, based on a novel moving virtual antenna array (MVAA) measurement scheme. The principle of the MVAA scheme is deeply investigated and is further verified by a theoretical geometry-based stochastic model. Using the MVAA scheme, virtual single-input multiple-output (SIMO) channel impulse response data are derived from single-antenna measurements in typical HSR scenarios, involving viaduct, cutting, and station. Based on the SIMO channel data, angle of arrival is extracted according to the unitary estimation of signal parameters by the rotational invariance techniques algorithm, and is compared with the theoretical result. Moreover, power angular spectrum and root mean square (rms) angular spread (AS) are provided, and the rms AS results are statistically modeled and comprehensively compared. In addition, spatial correlation is calculated and analyzed, and a rms AS-dependent spatial correlation model is newly proposed to describe the relationship between the angular dispersion and the spatial correlation. The presented results could be used in multi-antenna channel modeling and will facilitate the assessment of multi-antenna technologies for future HSR mobile communication systems.

New Solutions for Distributed Realization of 8 × 1 MISO channel with QOSTBC

We proposed new solutions for distributed realization of the quasi orthogonal space-time block coding (QOSTBC), which is designed for 8 × 1 multiple input–single output (MISO) system. The first proposed solution assumes that base station and relay stations are equipped with 2 antennas, while for the second solution base station is equipped with 4 antennas and relay stations are with one antenna. In both scenarios mobile unit is equipped with single antenna. The proposed solutions are compared with distributed QOSTBC which is used for 4 × 1 MISO system. The simulation results show BER performances improvements provided with the proposed solutions in comparison with distributed QOSTBC designed for 4 × 1 MISO. It was shown that the first proposed scheme provides lower BER values than the second solution. Also, beside ideal channel estimation, influence of real estimation errors on BER performances is considered.

The Capacity of Gaussian MIMO Channels Under Total and Per-Antenna Power Constraints

The capacity of a fixed Gaussian multiple-input multiple-output (MIMO) channel and the optimal transmission strategy under the total power (TP) constraint and full channel state information are well known. This problem remains open in the general case under individual per-antenna (PA) power constraints, while some special cases have been solved. These include a full-rank solution for the MIMO channel and a general solution for the multiple-input single-output (MISO) channel. In this paper, the fixed Gaussian MISO channel is considered and its capacity and optimal transmission strategies are determined in a closed form under the joint total and PA power constraints in the general case. In particular, the optimal strategy is hybrid and includes two parts: first is equal-gain transmission and second is maximum-ratio transmission, which are responsible for the PA and TP constraints, respectively. The optimal beamforming vector is given in a closed form and an accurate yet simple approximation to the capacity is proposed. Finally, the above results are extended to the MIMO case by establishing the ergodic capacity of fading MIMO channels under the joint power constraints when the fading distribution is right unitary-invariant (of which i.i.d. and semi-correlated Rayleigh fading are special cases). Unlike the fixed MISO case, the optimal signaling is shown to be isotropic in this case.