Time-invariant rateless codes for MIMO channels

The reconfigurable intelligent surface (RIS) is useful to effectively improve the coverage and data rate of end-to-end communications. In contrast to the well-studied coverage-extension use case, in this paper, multiple RIS panels are introduced, aiming to enhance the data rate of multi-input multi-output (MIMO) channels in presence of insufficient scattering. Specifically, via the operator-valued free probability theory, the asymptotic mutual information of the large-dimensional RIS-assisted MIMO channel is obtained under the Rician fading with Weichselberger’s correlation structure, in presence of both the direct and the reflected links. Although the mutual information of Rician MIMO channels scales linearly as the number of antennas and the signal-to-noise ratio (SNR) in decibels, numerical results show that it requires sufficiently large SNR, proportional to the Rician factor, in order to obtain the theoretically guaranteed linear improvement. This paper shows that the proposed multi-RIS deployment is especially effective to improve the mutual information of MIMO channels under the large Rician factor conditions. When the reflected links have similar arriving and departing angles across the RIS panels, a small number of RIS panels are sufficient to harness the spatial degree of freedom of the multi-RIS assisted MIMO channels.

In this paper, a new framework to characterize the tradeoff between diversity and multiplexing gains of Multi Input Multi Output (MIMO) wireless systems at finite Signal to Noise Ratios (SNRs) is presented. By suitable definitions of non-asymptotic diversity and multiplexing gains, we extract a useful tool to investigate the performance of space-time schemes at finite SNRs. Exact results on the diversity-multiplexing tradeoff (DMT) are derived for Multi Input Single Output (MISO), Single Input Multi Output (SIMO), and 2 × 2 MIMO channels. We show that our outcomes coincide with the Zheng and Tse's results at high SNRs. When the new definitions of non-asymptotic diversity and multiplexing gains are used, the resulted DMT converges to its asymptotic value at realistic SNRs. Furthermore, using these definitions enables the diversity gain to represent the outage probability with reasonable accuracy.

In a companion paper, we have studied the zero-forcing (ZF) transceiver with decision feedback equalizer (DFE) over slowly time-varying narrowband multiinput multioutput (MIMO) channels. The space-time generalized triangular decomposition (ST-GTD) was used for the design of ZF-DFE transceivers. The space-time geometric mean decomposition (ST-GMD) ZF transceiver minimizes both the arithmetic mean square error (MSE) at the feedback detector and the average uncoded bit error rate (BER) in moderate high signal-to-noise ratio (SNR). This paper addresses the design problem of DFE transceiver without zero-forcing constraint. In the first part, a channel independent temporal precoder is superimposed on the conventional block-wise GMD-based minimum mean square error (MMSE) DFE transceiver to take advantage of the temporal diversity. In the second part, ST-GTD is applied for the design of MMSE DFE transceivers. With accurate channel prediction and space-time powerloading, the proposed ST-GMD MMSE transceiver minimizes the arithmetic MSE at the feedack detector, and maximizes Gaussian mutual information. For practical applications, the ST-GTD MMSE transceiver which does not require channel prediction but shares the same asymptotic BER performance with the ST-GMD MMSE system is also developed. In the convex region, our analysis shows that the proposed MMSE transceivers has better BER performance than the conventional GMD-based MMSE transceiver; the average BERs of the proposed systems are nonincreasing functions of the ST-block size. The superior performance of ST-GMD MMSE transceiver over the ST-GMD ZF transceiver is also verified analytically.

In wireless communication, multiple signals are utilized to receive and send information in the form of signals simultaneously. These signals consume little power and are usually inexpensive, with a high data rate during data transmission. An Multi Input Multi Output (MIMO) system uses numerous antennas to enhance the functionality of the system. Moreover, system intricacy and power utilization are difficult and highly complicated tasks to achieve in an Analog to Digital Converter (ADC) at the receiver side. An infinite number of MIMO channels are used in wireless networks to improve efficiency with Cross Entropy Optimization (CEO). ADC is a serious issue because the data of the accepted signal are completely lost. ADC is used in the MIMO channels to overcome the above issues, but it is very hard to implement and design. So, an efficient way to enhance the estimation of channels in the MIMO system is proposed in this paper with the utilization of the heuristic-based optimization technique. The main task of the implemented channel prediction framework is to predict the channel coefficient of the MIMO system at the transmitter side based on the receiver side error ratio, which is obtained from feedback information using a Hybrid Serial Cascaded Network (HSCN). Then, this multi-scaled cascaded autoencoder is combined with Long Short Term Memory (LSTM) with an attention mechanism. The parameters in the developed Hybrid Serial Cascaded Multi-scale Autoencoder and Attention LSTM are optimized using the developed Hybrid Revised Position-based Wild Horse and Energy Valley Optimizer (RP-WHEVO) algorithm for minimizing the "Root Mean Square Error (RMSE), Bit Error Rate (BER) and Mean Square Error (MSE)" of the estimated channel. Various experiments were carried out to analyze the accomplishment of the developed MIMO model. It was visible from the tests that the developed model enhanced the convergence rate and prediction performance along with a reduction in the computational costs.

Achievable rate (AR) is significant to communications. As to multi-input multi-output (MIMO) digital transmissions with finite alphabets inputs, which greatly improve the performance of communications, it seems rather difficult to calculate accurate AR. Here we propose an estimation of con-siderable accuracy and low complexity, based on Euclidean measure matrix for given channel states and constellations. The main contribution is explicit expression, non-constraints to MIMO schemes and channel states and constellations, and controllable estimating gap. Numerical results show that the proposition is able to achieve enough accurate AR computation. In addition the estimating gap given by theoretical deduction is well agreed.

In this paper, we present an asymptotical analysis of channel capacity of Bell labs layered space-time (BLAST) architectures based on a zero-forcing(ZF) criterion in the sense of signal-to-noise ratio (SNR). We begin by introducing a new relationship related to multi-input multi-output (MIMO) channel capacity. We prove that Diagonal Bell Labs Space-Time (D-BLAST) attains the lower bound for MIMO channels when interference nulling is carried out based on the ZF-criterion. An exact closed-form expression for the probability density function of the channel capacity is analyzed. Based on the asymptotic behavior of the channel capacity of each layer, closed-form expressions for the asymptotic ergodic capacity are derived for BLAST. Based on the analysis presented in this paper, we gain an insight on the channel capacity behavior for a MIMO channel. Computer simulation results have verified the validity and accuracy of the proposed analysis for a wide range of antenna array sizes.

We study the performance of multi-input multi-output (MIMO) channels with coarsely quantized outputs in the low signal-to-noise ratio (SNR) regime, where the channel is perfectly known at the receiver. This analysis is of interest in the context of ultra-wideband (UWB) communications from two aspects. First the available power is spread over such a large frequency band, that the power spectral density is extremely low and thus the SNR is low. Second the analog-to-digital converters (ADCs) for such high bandwidth signals should be low-resolution, in order to reduce their cost and power consumption. In this paper we consider the extreme case of only 1-bit ADC for each receive signal component. We compute the mutual information up to second order in the SNR and study the impact of quantization. We show that, up to first order in SNR, the mutual information of the 1-bit quantized system degrades only by a factor of 2/pi compared to the system with infinite resolution independent of the actual MIMO channel realization. With channel state information (CSI) only at receiver, we show that QPSK is, up to the second order, the best among all distributions with independent components. We also elaborate on the ergodic capacity under this scheme in a Rayleigh flat-fading environment.

Multi-input multi-output (MIMO) technique is attractive for visible light communication (VLC), which exploits the high signal-to-noise ratio (SNR) of a single channel to overcome the capacity limitation due to the small modulation bandwidth of the light emitting diode. This paper establishes a MIMO VLC system under the non-negativity, peak power and dimmable average power constraints. Assume that perfect channel state information at the transmitter is known, the MIMO channel is changed to parallel, non-interfering sub-channels by using the singular value decomposition (SVD). Based on the SVD, the lower bound on the channel capacity for MIMO VLC is derived by employing entropy power inequality and variational method. Moreover, by maximizing the derived lower bound on the capacity under the given constraints, the receiver deployment optimization problem is formulated. The problem is solved by employing the principle of particle swarm optimization. Numerical results verify the derived capacity bound and the proposed deployment optimization scheme.

In this paper we study the fundamental limitations in stabilization and tracking of multi-input, multi-output (MIMO) networked feedback systems. We adopt a parallel additive white noise (AWN) model for the MIMO communication channel, and consider as our performance measure the mean square error for a system's output to track a random reference signal with finite power. Of particular interest in our study is the joint design of the controller and the channel to mitigate the requirement on feedback stabilization and to better the tracking performance. To this effect we consider scaled AWN channels, with positive diagonal scaling matrices interpreted as static coders and decoders. By casting the problem as a constrained optimal H 2 control problem and employing duality principles, we derive necessary and sufficient conditions for the system to be mean-square stabilizable and analytical characterizations for the best achievable performance under channel input power constraint. While fundamental limits are known to exist, it is seen that an appropriate channel scaling can be employed to exploit the channel power effectively so as to fundamentally improve a system's stabilizability and tracking performance.

The Spatial Modulation (SM) transmission scheme boosts the spectral efficiency and achieves the multiplexing gain by activating a single transmit antenna in each time slot. Radio wave propagation characteristics determined by the environment is a decisive factor for the SM system. In this paper, we investigate the performance of the SM scheme over real-world 4×4 Multi-Input Multi-Output (MIMO) channels measured in typical indoor scenarios. Firstly, a MIMO channel sounder is established. Based on the sounder, 15150 complex 4×4 MIMO channel matrices are measured inside a typical teaching building under both Line of Sight (LOS) and None Line of Sight (NLOS) scenarios. Secondly, by comparing the SM system over the measured channel and commonly-used channel models, we prove that both the Independently and Identically Distribute (i.i.d.) Rayleigh and the Spatial Correlation (SC) channel model are oversimplified, and that only practical experiences can yield definitive answers to the achievable real-world system performance. Thirdly, the Average Bit Error Probability (ABEP) performance of the SM system is studied based on the measured data under a variety of system configurations. The study of different receive antenna array settings (4×4, 4×2 and 4×1 MIMO setups) approves the significance of combining scheme at the receiver. SM systems employing different signal constellations (Binary Phase Shift Keying (BPSK), Quadrature Phase Shift Keying (QPSK) and 16 Quadrature Amplitude Modulation (16QAM)) are also investigated and some interesting results are revealed. Lastly, performance assessment of SM against State-Of-The-Art (SOTA) MIMO schemes (Space-Time Block Code (STBC) and Vertical Bell Labs Layered Space-Time (V-BLAST) code) is conducted. Results show that for a 4×4 MIMO, the low-complexity SM scheme outperforms both STBC and V-BLAST.

We examine the multi-input multi-output (MIMO) channel capacity where one side of the link constitutes a largely spaced antenna array, e.g. distributed antenna system (DAS), which prompts the need to model the channel that has both microscopic and macroscopic fading. Specifically, we consider a MIMO system comprising M antennas co-located at one side of the link and N largely separated ports each with L antennas colocated within a port at the other, named as generalized distributed antenna system (GDAS). We assume independent macroscopic and microscopic fading between ports and common macroscopic but independent microscopic fading at each antenna in a port. Using a simple composite fading channel model, a Rayleigh-lognormal composite fading, the influence of the macroscopic diversity as well as the microscopic diversity on the channel capacity, especially the outage capacity, of the MIMO GDAS is investigated for both the uplink and the downlink.

Measurement campaigns have indicated that propagation paths with multiple reflections are important in indoor and picocell environments. It has also been found that it is difficult to match both angles and delays using single-bounce models. A double-bounce multi-input multi-output (MIMO) channel model is proposed that also includes polarization. The scattering geometry based channel model is extended to two scattering instants per path, i.e. double-bounce, in order to model indoor and picocell environments better. Formulas for determining the required positions of the scatterers in order to yield a desired angular spread are derived under the double-bounce assumption. Furthermore, a physics based full field treatment of the polarization properties of the antennas is possible since the scattering geometry based models keep the same physical layout as the experiments. The validity of the model is examined by comparing simulations of the channel capacity to measurements taken with a MIMO channel probing equipment at the campus of Brigham Young University.

The capacity of downlink multi-input multi-output (MIMO) systems is significantly limited by inter-cell co-channel interference (CCI). Improving the performance of cell edge users who suffers strong inter-cell CCI is still a crucial issue. In this paper, coordinated beamforming (CBF) algorithm for multicell multiuser MIMO system is proposed to cope with the presence of intel-cell CCI. In multicell environment with MIMO channel, limited base station (BS) cooperation is considered to design optimal transmit and receive beamformers which make interference-free at the receiver. Simulation results show that the proposed algorithms can improve the capacity of cell edge user effectively as well as the overall system capacity for multiuser multicell MIMO system.

In this paper the multi-input multi-output (MIMO) channel characteristics of a typical office environment are with a 4×4 MIMO channel sounder at 2.35GHz with 100MHz band-width. The objective of this work is to obtain a better assessment of the potentials of indoor communications by characterizing the wideband indoor channels. We focus on the characteristics of time dispersion and correlation with multiple polarized antennas. For different scenarios, the channel capacity is also analyzed. Finally, the reciprocity of delay spread and multipath is investigated.

We consider a block fading frequency selective multi-input multi-output (MIMO) channel in additive white Gaussian noise (AWGN). The channel input is a training vector superimposed on a linearly precoded vector of Gaussian symbols. This form of precoding is referred to as affine precoding. We derive the Cramer-Rao bound (CRB) under two circumstances: the random parameter vector to be estimated contains (i) only fading channel coefficients, (ii) unknown data symbols as well as the channel coefficients. While case (i) corresponds to the decoding schemes in which the channel is estimated first and the channel measurement is utilized to recover the data symbols, case (ii) corresponds to methods in which channel and symbol estimation is performed jointly. The interesting outcome of our investigation is that minimizing trace of the channel CRB for cases (i) and (ii) under a total transmit power constraint leads to different affine precoder design guidelines.