Full-diversity iterative MMSE receivers with space-time precoders over block-fading MIMO channels

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 this contribution, we investigate the performance of dual-polarized multi input multi output (MIMO) multi-carrier interleave division multiple access system (MC-IDMA) over correlated frequency selective channels in the presence of channel state estimation error. In the code division multiple access (CDMA), orthogonal spreading sequence is used as user specific where as in IDMA, user specific interleaving pattern is used. In our considered work, Multi-carrier (MC) is realized by orthogonal frequency division multiplexing (OFDM). The channel is estimated at the mobile stations (MSs) by pilot assisted channel estimation (PACE) technique using minimum mean square error (MMSE) algorithm. Further, the dual-polarized MIMO system considered in our work which is realized with the aid of orthogonal polarizations, replaces two spatially separated uni-polarized antennas, thus resulting in polarization multiplexing. In particular, we evaluate the effects of three types of delay spread on MIMO MC-IDMA system in the context of downlink (DL) communications pertaining to the Standard University Interim (SUI) channel model. In a multi-user environment, users experience multi stream interference (MSI) in addition to the multiple access interference (MAI) and these interferences can degrade the system performance. Furthermore, we consider turbo code as channel encoder for MIMO MC-IDMA system to mitigate the effects of MAI and MSI. It is discerned from the simulation results that dual-polarized MIMO MC-IDMA system is capable of supporting many users and performs better in terms of achievable bit error rate (BER) in the context of DL communications with reduced number of antennas.

Multi input multi output (MIMO) system with the multiple antennas at both the transmitter and receiver is the emerging technology in the modern wireless system. MIMO systems are well adopted due to its high spectral efficiency and high data rates. For the detection of MIMO systems, a powerful technique called Lattice Reduction (LR) algorithm are used to obtain the better orthogonality in the channel matrices and is aided with the linear and low complexity detectors such as Zero forcing(ZF) and Minimum mean square error (MMSE) for the reduction in complexity. In this paper we propose a new algorithm called Enhanced lattice reduction algorithm to improve the error performance for the linear detectors with the lesser complexity and also it is aided with the non linear precoding called Tomlinson-Harashima precoding (THP) in the presence of channel state information (CSI). Lattice reduction aided with THP improves the performance linearly. BER performance of the proposed algorithm is determined and it is compared with the other LR aided algorithms in the literature.

Performance analysis of multicell multiuser MIMO MC DS/CDMA system with MMSE user-ordered SIC technique

Adaptive beamforming is capable of separating user signals transmitted on the same carrier frequency, and thus provides a practical means of supporting multiusers in a space-division multiple-access scenario. Moreover, for the sake of further improving the achievable bandwidth efficiency, high-throughput quadrature amplitude modulation (QAM) schemes have become popular in numerous wireless network standards, notably, in the recent WiMax standard. This contribution focuses on the design of adaptive beamforming assisted detection for the employment in multiple-antenna aided multiuser systems that employ the high-order QAM signalling. Traditionally, the minimum mean square error (MMSE) design is regarded as the state-of-the-art for adaptive beamforming assisted receiver. However, the recent work (Chen et al., 2006) proposed a novel minimum symbol error rate (MSER) design for the beamforming assisted receiver, and it was demonstrated that this MSER design provides significant performance enhancement, in terms of achievable symbol error rate, over the standard MMSE design. This MSER beamforming design is developed fully in this contribution. In particular, an adaptive implementation of the MSER beamforming solution, referred to as the least symbol error rate algorithm, is investigated extensively. The proposed adaptive MSER beamforming scheme is evaluated in simulation, in comparison with the adaptive MMSE beamforming benchmark.

In cooperative communications, due to the distributed nature, multiple different carrier frequency offsets (CFOs) may occur and make the channel time-varying. It is hard for the receiver to compensate multiple CFOs from multiple relay nodes simultaneously. Thus, the conventional space-time codes to collect cooperative diversity for co-located multi-input multi-output (MIMO) systems may not be applied directly. In this paper, we consider the cooperative transmission with multiple CFOs when the channels from relay nodes to destination node are flat (frequency-non-selective) fading. We approximate a flat fading channel with CFO as a block time-invariant intersymbol-interference (ISI) channel in the frequency domain. We then propose two distributed space-frequency codes (SFC) for such ISI channels in the frequency domain to achieve the cooperative full spatial diversity, where the space-frequency coding concept is different from the one in the literature and also has a different role. One is called frequency-reversal SFC and the other is called frequency-domain linear convolutive SFC. Furthermore, we show that, with only linear receivers, such as zero-forcing (ZF) and minimum mean square error (MMSE) receivers, our codes achieve the full cooperative diversity.

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.

We propose an improved minimum mean square error (MMSE) vertical Bell Labs layered space-time (V-BLAST) detection technique, called a soft input, soft output, and soft feedback (SIOF) V-BLAST detector, for turbo multi-input multioutput (turbo-MIMO) systems. We derive a symbol estimator by minimizing the power of the interference plus noise, given a priori probabilities of undetected layer symbols and a posteriori probabilities for past detected layer symbols. For a low-complexity implementation, an approximate SIOF algorithm is presented, which allows for a time-invariant realization of the symbol ordering and an MMSE filtering process. Another implementation, referred to as the iterative SIOF algorithm is introduced, which decides on symbol detection order based on a posteriori symbol probabilities to improve the detection performance. Simulations performed on a space-time bit-interleaved coded modulation (STBICM) architecture over quasi-static MIMO fading channels demonstrate that the SIOF V-BLAST detector provides performance gains over previous turbo-BLAST detectors, most notably when more transmit antennas are used.

3GPP (3rd Generation Partnership Project) LTE (Long Term Evolution) Advanced standards are currently under way, where 4×4 MIMO (Multiple Input Multiple Output) scheme is the minimum structure. One of the best solutions to support the maximum data rate transmission is to adopt a MIMO scheme, especially spatial multiplexing mode, which means that each antenna port can transmit separate data. To realize this algorithm, the main issue is to cancel interferences added to each antenna port, and therefore, the algorithm at the receiver should have good performances. In the aspect of implementation, MMSE (Minimum Mean Square Error) detection algorithm is a reasonable method considering both complexity and performance. Furthermore, an iterative receiver (IR) algorithm can also be applied to this system. An IR algorithm has a tradeoff between complexity and performance. In this paper, we designed a reasonable and implementable MIMO receiver structure and showed performance for 3GPP LTE Advanced system, and verified that hard decoded bits, PIC-MMSE (Parallel Interference Cancellation - MMSE) and 1-iteration PIC are enough to meet the required SNR using the implemented test-bed system.

In this thesis, we cope with the fundamental mathematical and physical problems of the space-time-Doppler UWB system design for fading channels: multi-input multi-output (MIMO) wireless communication with adaptive filtering. The estimation algorithm from equalizer providing an accurate parameters estimate is investigated. UWB radio is a fast emerging technology with uniquely attractively features inviting major advances in wireless communications, networking, radar, imaging, and positioning systems. By its rule-making proposal in 2002, the Federal Communications Commission (FCC) in the United States essentially unleashed huge new bandwidth (3.6-10.6 GHz) at the noise floor, where UWB radios overlaying coexistence RF systems cerate using low-power ultra-short information bearing pulses. Right now, there are three basic types of UWB: multiband OFDM UWB (MB-OFDM UWB), impulse-UWB (I-UWB), and direct sequence UWB (DS-UWB). We focus on I-UWB and MB-OFDM-UWB, and compare their performance. A simple means for spreading the spectrum of low duty cycle pulse trains is time hopping (TH), with pulse position modulation (PPM) for data modulation at the rate of many pulses per data bit. The main contribution of this thesis for I-UWB is the design of leading edge detectors, coherent correlation detector (CCD), and pilot performance enhancement compared with different Rayleigh and Ricean fading conditions. For MB-OFDM UWB, we have considered the performance analysis and design criteria of MIMO OFDM UWB systems for high data-rate wireless transmission. The signal processing of frame detection, time synchronization, frequency synchronization, channel estimation, synchronization tracking using pilot subcarriers and 2-D MIMO detection algorithms is discussed. The main contributions of this thesis are 1) Compared with receiver employing the Maximum Likelihood (ML) detector, the receiver employing a low-complexity linear Minimum Mean Square Error (MMSE) demodulator can perform a limited performance loss in spatially uncorrelated channels. 2) Due to the operations of spreading and dispreading combined with MMSE-based frequency domain equalization, the adverse effects of the low-SNR subcarriers on the average BER performance are potentially improved. This is a direct consequence of spreading, because even if the signal corresponding to a specific chip is obliterated by a deep frequency domain channel fade, after dispreading these effects are spread over the Walsh-Hadamard Transform (WHT) length. Hence there is a high chance of still recovering all the partially affected subcarrier symbols without errors. 3) As a test case, the OFDM-based 200 Mb/s MB-UWB network (IEEE 802.15.3a) are considered, but the simulation results are shown above section. 4) The simulation channel can be easily applied to NOS and NLOS situation with WHT transformation from Simulink model. The fading channels of UWB with low/high signal to noise ratio (SNR), multipath effects, and multiuser interference may introduce large errors in location. The location engine performs the following tasks: █ Data fusion techniques: Different data fusion techniques are implemented using Time Of Arrival (TOA), Angle Of Arrival (AOA), or a combination of both. █ Channel modeling: A multipath, multiuser channel environment is created that models path loss, shadowing, Rayleigh fading, and Doppler frequency effects. █ Parameter estimation: TOA and AOA estimation algorithms are implemented as part of the location finding engine. Different variations of algorithms are implemented for performance and comparison purposes. █ Configuring the physical layer for different wireless networks. Among the programmable parameters are spreading factor, packet size, training length, constellation type, modulation technique, carrier frequency, level of transmitted signal power, and the number of antennas at the transmitter for both sides. █ Configuring the mobile user conditions. The wireless channel models depend on the Doppler frequencies present in the environment. The Doppler frequency depends on the mobile speed and carrier frequencies as input and generates a Rayleigh fading channel with the U-shape Doppler spectrum. █ Configuring the environmental parameters and network geographical structure. One of the factors affecting the performance of the wireless location system is the environment type (e.g., bad urban, urban, suburban, or rural area). For example, in a bad urban area with many blocking objects and buildings, non-line of sight (NLOS) effects plays an important role in the estimation accuracy.

General-purpose processor (GPP), which is suitable for software radio processing because of its powerful processing capability and flexibility, has aroused industry-wide attention and exploration. By taking advantage of streaming single instruction multiple data extensions (SSE), this paper presents the GPP-based design of multi-input multi-output (MIMO) detection which is of high complexity in LTE downlink receiver. The performance simulation results illustrate that with dramatically reduced complexity soft minimum mean square error (MMSE) detection is able to approximate ML performance in low signal-to-noise-ratio (SNR), and about 4 dB lose in high SNR. The complexity comparison results show that the implementation of soft MMSE detection in parallel can reduce the processing time by about 86% compared with not in parallel.

In the next Japanese digital terrestrial television broadcasting systems, the scheme that combines orthogonal frequency division multiplexing (OFDM) and dual-polarized multi-input multi-output (MIMO) is proposed. One of the major problems to be considered is inter-carrier interference (ICI) that is generated by Doppler-spread under mobile reception of MIMO-OFDM systems. In this case, reception characteristics are deteriorated significantly. The ICI canceller for MIMO-OFDM can demodulate transmitted symbols. To realize the MIMO-ICI canceller based on zero-forcing (ZF), it is necessary to reduce the complex calculations such as matrix operations. Therefore, complexity reduction of the MIMO-ICI canceller is proposed. The proposed MIMO-ICI canceller with complexity reduction based on ZF can improve the influence of ICI with low complexity. However, reception characteristics are deteriorated as compared to the MIMO-ICI canceller based on ZF. Thus, improving scheme of MIMO-ICI canceller with complexity reduction based on ZF is proposed. In the proposed scheme, the iterative detection is adopted. In addition, MIMO-ICI cancellers based on minimum mean square error (MMSE) are proposed. As the results of computer simulations, the MIMO-ICI cancellers using iterative detection based on ZF and MMSE can improve the reception characteristics with low complexity.

Optimal receiver diversity combining employing linear channel estimation is examined. Based on the statistical properties of least-squares (LS) and minimum mean square error (MMSE) channel estimation, an optimal diversity receiver for wireless systems employing practical linear channel estimation on Rician fading channels is proposed. The new receiver structure includes the conventional maximal ratio combining receiver as a special case. Exact analytical expressions for the symbol error rates (SERs) of LS and MMSE channel estimation aided optimal diversity combining are derived. It is shown that, if an optimal detector is used, an MPSK wireless system with MMSE channel estimation has the same SER when the MMSE channel estimation is replaced by LS estimation. This is an interesting counterexample to the common perception that channel estimation with smaller mean square error leads to smaller SER. Extensive simulation results validate the theoretical results.

SummaryIn this work, a deep learning (DL)‐based massive multiple‐input multiple‐output (mMIMO) orthogonal frequency division multiplexing (OFDM) system is investigated over the tapped delay line type C (TDL‐C) model with a Rayleigh fading distribution at frequencies ranging from 0.5 to 100 GHz. The proposed bi‐directional long short‐term memory (Bi‐LSTM) channel state information (CSI) estimator uses online learning during training and offline learning during the practical implementation phase. The design of the estimator takes into account situations in which prior knowledge of channel statistics is limited and targets excellent performance, even with limited pilot symbols (PS). Three separate loss functions (mean square logarithmic error [MSLE], Huber, and Kullback–Leibler Distance [KLD]) are assessed in three classification layers. The symbol error rate (SER) and outage probability performance of the proposed estimator are evaluated using a number of optimization techniques, such as stochastic gradient descent (SGD), momentum, and the adaptive gradient (AdaGrad) algorithm. The Bi‐LSTM‐based CSI estimator is trained considering a specific number of PS. It can be readily seen that by incorporating a cyclic prefix (CP), the system becomes more resilient to channel impairments, resulting in a lower SER. Simulations show that the SGD optimization approach and Huber loss function‐trained Bi‐LSTM‐based CSI estimator have the lowest SER and very high estimation accuracy. By using deep neural networks (DNNs), the Bi‐LSTM method for CSI estimation achieves a superior channel capacity (in bps/Hz) at 10 dB than long short‐term memory (LSTM) and other conventional CSI estimators, such as minimum mean square error (MMSE) and least squares (LS). The simulation results validate the analytical results in the study.

In this letter, we present a linear precoder design scheme for a cognitive (CR) multi-input multi-output (MIMO) system, where a secondary broadcast channel uses the same spectrum with multiple primary users (PUs). Considering both cooperative feedback from the PUs and local feedback from the secondary users (SUs) to the secondary transmitter (ST), the ST can obtain the quantized information regarding the direction of the channels. The proposed scheme is based on the minimum mean square error (MMSE) criteria and is robust to the channel uncertainties caused by quantization error. The derivation is given under two different levels of interference constraints respectively. Simulation results show the effectiveness of the proposed precoder design scheme.