In this paper, we propose a new algorithm of iterative least squared (LS) channel estimation for 64 antennas Massive Multiple Input, Multiple Output (MIMO) turbo-receiver. The algorithm employs log-likelihood ratios (LLR) of low-density parity-check (LDPC) decoder and minimum mean square error (MMSE) estimator to achieve soft data symbols. These soft data symbols are further MMSE-weighted again and combined with pilot symbols to achieve a modified LS channel estimate. The modified LS estimate is employed by the same channel estimation unit to enhance turbo-receiver performance via channel re-estimation, as a result, the proposed approach has low complexity and fits any channel estimation solution, which is quite valuable in practice. We analyze both hard and soft algorithm versions and present simulation results of 5G turbo-receiver in the 3D-UMa model of the QuaDRiGa 2.0 channel. Simulation results demonstrate up to 0.3dB performance gain compared to the unweighted hard data symbols utilization in the LS channel re-calculation.
We investigate a turbo soft detector based on the expectation propagation (EP) algorithm for large-scale multiple-input multiple-output (MIMO) systems. Optimal detection in MIMO systems becomes computationally unfeasible for high-order modulations and/or large number of antennas. In this situation, the linear minimum mean square error (LMMSE) exhibits a low-complexity with a good performance, however far from optimal. To improve the performance, the EP algorithm can be used. In this paper, we review previous EP-based detectors and enhance their estimation in terms of complexity and performance…
Precoding is a method of compensating the channel at the transmitter. This work presents a novel method of data detection in turbo coded single user massive multiple input multiple output (MIMO) systems using precoding. We show via computer simulations that, when precoding is used, re-transmitting the data does not result in significant reduction in bit-error-rate (BER), thus increasing the spectral efficiency, compared to the case without precoding. Moreover, increasing the number of transmit and receive antennas results in improved BER.
Large beam training overhead has been considered as one of main issues in the channel estimation for reconfigurable intelligent surface (RIS)-aided systems. In this paper, we propose an atomic norm minimization (ANM)-based low-overhead channel estimation for RIS-aided multiple-input-multiple-output (MIMO) systems. When the number of beam training is reduced, some multipath signals may not be received during beam training, and this causes channel estimation failure. To solve this issue, the width of beams created by RIS is widened to capture all multipath signals. Pilot signals received during …
In this paper, we propose a novel joint caching and massive multiple-input multiple-output (MIMO) transmission scheme, referred to as cache-aided massive MIMO, for advanced downlink cellular communications. In addition to reaping the conventional advantages of caching and massive MIMO, the proposed scheme also exploits the side information provided by cached files for interference cancellation at the receivers. This interference cancellation increases the degrees of freedom available for precoding design. In addition, the power freed by the cache-enabled offloading can benefit the transmission…
Turbo codes and CRC codes are usually decoded separately according to the serially concatenated inner codes and outer codes respectively. In this letter, we propose a hybrid decoding algorithm of turbo-CRC codes, where the outer codes, CRC codes, are not used for error detection but as an assistance to improve the error correction performance. Two independent iterative decoding and reliability based decoding are carried out in a hybrid schedule, which can efficiently decode the two different codes as an entire codeword. By introducing an efficient error detecting method based on normalized Euc…
We consider the channel estimation problem in point-to-point reconfigurable intelligent surface (RIS)-aided millimeter-wave (mmWave) MIMO systems. By exploiting the low-rank nature of mmWave channels in the angular domains, we propose a non-iterative Two-stage RIS-aided Channel Estimation (TRICE) framework, where every stage is formulated as a multidimensional direction-of-arrival (DOA) estimation problem. As a result, our TRICE framework is very general in the sense that any efficient multidimensional DOA estimation solution can be readily used in every stage to estimate the associated channe…
In this paper, we analyze the performance of evolutionary heuristic-aided linear detectors deployed in Multiple-Input Multiple-Output (MIMO) Orthogonal Frequency-Division Multiplexing (OFDM) systems, considering realistic operating scenarios. Hybrid linear-heuristic detectors under different initial solutions provided by linear detectors are considered, namely differential evolution (DE) and particle swarm optimization (PSO). Numerical results demonstrated the applicability of hybrid detection approach, which can improve considerably the performance of minimum mean-square error (MMSE) and matc…
Reconfigurable intelligent surfaces (RISs) have been proposed recently as new technology to tune the wireless propagation channels in real-time. However, most of the current works assume single-RIS (S-RIS)-aided systems, which can be limited in some application scenarios where a transmitter might need a multi-RIS-aided channel to communicate with a receiver. In this paper, we consider a double-RIS (D-RIS)-aided MIMO system and propose an alternating least-squared-based channel estimation method by exploiting the Tucker2 tensor structure of the received signals. Using the proposed method, the c…
Reconfigurable intelligent surface (RIS) technology has recently emerged as a spectral- and cost-efficient approach for wireless communications systems. However, existing hand-engineered schemes for passive beamforming design and optimization of RIS, such as the alternating optimization (AO) approaches, require a high computational complexity, especially for multiple-input-multiple-output (MIMO) systems. To overcome this challenge, we propose a low-complexity unsupervised learning scheme, referred to as learning-phase-shift neural network (LPSNet), to efficiently find the solution to the spect…
This paper derives a novel pilot-aided phase and channel estimation algorithm for multiple-input multiple-output (MIMO) systems with phase noise and quasi-static channel fading. Our novel approach allows, for the first time, carrier phase estimation and recovery to be performed before full channel estimation. This in turn enables the channel estimation to be calculated using the whole frame, significantly improving its accuracy. The proposed algorithm is a sequential combination of several linear algorithms, which greatly reduces the computational complexity. Moreover, we also derive, for the …
Multi-input multi-output orthogonal frequency division multiplexing (MIMO OFDM) is a key technology for mobile communication systems. However, due to the issue of high peak-to-average power ratio (PAPR), the OFDM symbols may suffer from nonlinear distortions of the power amplifier (PA) at the transmitters, which degrades the channel estimation and detection performances of the receivers. To mitigate the clipping distortions at the receivers end, we leverage deep learning (DL) and devise a DL based receiver which is aided by the traditional least square (LS) channel estimation and the zero-forc…
Deep neural networks (NNs) have exhibited considerable potential for efficiently balancing the performance and complexity of multiple-input and multiple-output (MIMO) detectors. We propose a receiver framework that enables efficient online training by leveraging the following simple observation: although NN parameters should adapt to channels, not all of them are channel-sensitive. In particular, we use a deep unfolded NN structure that represents iterative algorithms in signal detection and channel decoding modules as multi layer deep feed forward networks. An expectation propagation (EP) mod…
In this correspondence, we propose a space domain index modulation (IM) scheme for the downlink of multiuser multiple-input multiple-output (MU-MIMO) systems. Instead of the most common approach where spatial bits select active receiver antennas, in the presented scheme the spatial information is mapped onto the transmitter side. This allows IM to better exploit large dimensional antenna settings which are typically easier to deploy at the base station. In order to mitigate inter-user interference and allow single user detection, a precoder is adopted at the BS. Furthermore two alternative enh…
This work studies a low-complexity design for reconfigurable intelligent surface (RIS)-aided multiuser multiple-input multiple-output systems. The base station (BS) applies receive antenna selection to connect a subset of its antennas to the available radio frequency chains. For this setting, the BS switching network, uplink precoders, and RIS phase-shifts are jointly designed, such that the uplink sum-rate is maximized. The principle design problem reduces to an NP-hard mixed-integer optimization. We hence invoke the weighted minimum mean squared error technique and the penalty dual decomposi…
Although it is often used in the orthogonal frequency division multiplexing (OFDM) systems, application of massive multiple-input multiple-output (MIMO) over the orthogonal time frequency space (OTFS) modulation could suffer from enormous training overhead in high mobility scenarios. In this paper, we propose one uplink-aided high mobility downlink channel estimation scheme for the massive MIMO-OTFS networks. Specifically, we firstly formulate the time domain massive MIMO-OTFS signal model along the uplink and adopt the expectation maximization based variational Bayesian (EM-VB) framework to r…
Reconfigurable Intelligent Surface (RIS) is considered as an energy-efficient solution for future wireless communication networks due to its fast and low-cost configuration. In this letter, we consider the estimation of cascaded channels in a double-RIS aided massive multiple-input multiple-output system, which is a critical challenge due to the large number of antennas equipped at the base station and passive RIS elements. To tackle this challenge, we propose a skip-connection attention (SC-attention) network that utilizes self-attention layers and skip-connection structure to improve the cha…
In this paper, we study the user localization and tracking problem in the reconfigurable intelligent surface (RIS) aided multiple-input multiple-output (MIMO) system, where a multi-antenna base station (BS) and multiple RISs are deployed to assist the localization and tracking of a multi-antenna user. By establishing a probability transition model for user mobility, we develop a message-passing algorithm, termed the Bayesian user localization and tracking (BULT) algorithm, to estimate and track the user position and the angle-of-arrival (AoAs) at the user in an online fashion. We also derive B…
Short range channels commonly arise in millimeter wave (mmWave) wearable settings, where the length of the antenna arrays can be comparable to the distance between the radios. Conventional mmWave MIMO channel estimation techniques based on the far field assumption may perform poorly in short range settings due to the large angular spread and, hence, high available rank. We propose a geometry-aided message passing algorithm that exploits structure in short range line-of-sight (LoS) channels for spatial sub-Nyquist channel estimation. Our approach parametrizes the channel using angle-of-arrivals…
Hybrid transceiver design in multiple-input multiple-output (MIMO) Tera-Hertz (THz) systems relying on sparse channel state information (CSI) estimation techniques is conceived. To begin with, a practical MIMO channel model is developed for the THz band that incorporates its molecular absorption and reflection losses, as well as its non-line-of-sight (NLoS) rays associated with its diffused components. Subsequently, a novel CSI estimation model is derived by exploiting the angular-sparsity of the THz MIMO channel. Then an orthogonal matching pursuit (OMP)-based framework is conceived, followed…
This paper analyzes transmit antenna selection (TAS) under Rayleigh flat fading for BPSK/QPSK modulations in multiple-input multiple-output wiretap channels, also termed as multiple-input multiple-output multiple-eavesdropper (MIMOME) channels. In our protocol, a single antenna is selected to transmit the secret message and selection combing (SC) or maximal-ratio combing (MRC) is utilized at the legitimate receiver or the eavesdropper. Novel closed-form expressions for the ergodic secrecy rates are derived to approximate the exact values, which hold high precision and compact forms. Besides th…
Reconfigurable intelligent surfaces (RISs) have been introduced as a remedy for mitigating frequent blockages in millimeter wave (mmWave) multiple-input multiple-output (MIMO) communication networks. However, perfect or nearly perfect channel state information (CSI) is fundamental in order to achieve their full potential. Traditionally, an RIS is fully passive without any baseband processing capabilities, which poses great challenges for CSI acquisition. Thus, we focus on the hybrid RIS architecture, where a small portion of RIS elements are active and able to processing the received pilot sig…
Reconfigurable Intelligent Surfaces (RISs) are regarded as a key technology for future wireless communications, enabling programmable radio propagation environments. However, the passive reflecting feature of RISs induces notable challenges on channel estimation, making coherent symbol detection a challenging task. In this paper, we consider the uplink of RIS-aided multi-user Multiple-Input Multiple-Output (MIMO) systems and propose a Machine Learning (ML) approach to jointly design the multi-antenna receiver and configure the RIS reflection coefficients, which does not require explicit full k…
This paper studies the secrecy performance of multiple-input multiple-output (MIMO) wiretap channels, also termed as multiple-input multiple-output multiple-eavesdropper (MIMOME) channels, under transmit antenna selection (TAS) and BPSK/QPSK modulations. In the main channel between the transmitter and the legitimate receiver, a single transmit antenna is selected to maximizes the instantaneous Signal to Noise Ratio (SNR) at the receiver. At the receiver and the eavesdropper, selection combination (SC) is utilized. By assuming Rayleigh flat fading, we first derive the closed-form approximated e…
In this paper, a data-driven position-aided approach is proposed to reduce the training overhead in MIMO systems, by leveraging side information and on-the-field measurements. A data tensor is constructed by collecting beam-training measurements on a subset of positions and beams, and a hybrid noisy tensor completion (HNTC) algorithm is proposed to predict the received power across the coverage area, which exploits both the spatial smoothness and the low-rank property of MIMO channels. A recommendation algorithm based on the completed tensor, beam subset selection (BSS), is proposed to achieve…
This paper considers an uplink reconfigurable intelligent surface (RIS)-aided massive multiple-input multiple-output (MIMO) system with statistical channel state information (CSI). The RIS is deployed to help conventional massive MIMO networks serve the users in the dead zone. We consider the Rician channel model and exploit the long-time statistical CSI to design the phase shifts of the RIS, while the maximum ratio combination (MRC) technique is applied for the active beamforming at the base station (BS) relying on the instantaneous CSI. Firstly, we reveal the power scaling laws and derive th…
In this work, we consider both channel estimation and reflection design problems in point-to-point reconfigurable intelligent surface (RIS)-aided millimeter-wave (mmWave) MIMO communication systems. First, we show that by exploiting the low-rank nature of mmWave MIMO channels, the received training signals can be written as a low-rank multi-way tensor admitting a canonical polyadic CP decomposition. Utilizing such a structure, a tensor-based RIS channel estimation method (termed TenRICE) is proposed, wherein the tensor factor matrices are estimated using an alternating least squares method. Us…
Terahertz (THz) systems have the benefit of high bandwidth and hence are capable of supporting ultra-high data rates, albeit at the cost of high pathloss. Hence they tend to harness high-gain beamforming. Therefore a novel hybrid 3D beamformer relying on sophisticated sensor-based beam training and channel estimation is proposed for Reconfigurable Intelligent Surface (RIS) aided THz MIMO systems. A so-called array-of-subarray based THz BS architecture is adopted and the corresponding sub-RIS structure is proposed. The BS, RIS and receiver antenna arrays of the users are all uniform planar arra…
Accurate channel estimation is essential to achieve the performance gains promised by the use of reconfigurable intelligent surfaces (RISs) in wireless communications. In the uplink of multi-user orthogonal frequency division multiple access (OFDMA) systems, synchronization errors such as carrier frequency offsets (CFOs) can significantly degrade the channel estimation performance. This becomes more critical in RIS-aided communications, as even a small channel estimation error leads to a significant performance loss. Motivated by this, we propose a joint CFO and channel estimation method for R…
Data-aided channel estimation is a promising solution to improve channel estimation accuracy by exploiting data symbols as pilot signals for updating an initial channel estimate. In this paper, we propose a semi-data-aided channel estimator for multiple-input multiple-output communication systems. Our strategy is to leverage reinforcement learning (RL) for selecting reliable detected symbols among the symbols in the first part of transmitted data block. This strategy facilitates an update of the channel estimate before the end of data block transmission and therefore achieves a significant red…
This work deals with turbo coded single user massive multiple input multiple output (SU-MMIMO) systems, with and without precoding. SU-MMIMO has a much higher spectral efficiency compared to multi-user massive MIMO (MU-MMIMO) since independent signals are transmitted from each of the antenna elements (spatial multiplexing). MU-MMIMO that uses beamforming has a much lower spectral efficiency, since the same signal (with a delay) is transmitted from each of the antenna elements. In this work, expressions for the upper bound on the average signal-to-noise ratio (SNR) per bit and spectral efficien…
This paper investigates the performance of reconfigurable intelligent surface (RIS)-aided massive multiple-input multiple-output (MIMO) systems with direct links, and the phase shifts of the RIS are designed based on the statistical channel state information (CSI). We first derive the closed-form expression of the uplink ergodic data rate. Then, based on the derived expression, we use the genetic algorithm (GA) to solve the sum data rate maximization problem. With low-complexity maximal-ratio combination (MRC) and low-overhead statistical CSI-based scheme, we validate that the RIS can still br…
Reconfigurable intelligent surface (RIS) has recently drawn intensive attention due to its potential of simultaneously realizing high spectral and energy efficiency in a sustainable way. This paper focuses on the design of efficient transmission methods to maximize the uplink sum throughput in a RIS-aided multi-user multi-input multi-output (MU-MIMO) system. To provide an insightful basis, the channel capacity of RIS-aided MU-MIMO is theoretically analyzed. Then, the conventional transmission schemes based on orthogonal multiple access are presented as the baseline. From the information-theore…
We consider a reconfigurable intelligent surface (RIS)-aided massive multi-user multiple-input multiple-output (MIMO) communication system with transceiver hardware impairments (HWIs) and RIS phase noise. Different from the existing contributions, the phase shifts of the RIS are designed based on the long-term angle informations. Firstly, an approximate analytical expression of the uplink achievable rate is derived. Then, we use genetic algorithm (GA) to maximize the sum rate and the minimum date rate. Finally, we show that it is crucial to take HWIs into account when designing the phase shift…
