Technology for sixth-generation (6G) mobile communication system is now being widely studied. A sub-Terahertz band is expected to play a great role in 6G to enable extremely high data-rate transmission. This paper has two goals. (1) Introduction of 6G concept and propagation characteristics of sub-Terahertz-band radio waves. (2) Performance evaluation of intelligent reflecting surfaces (IRSs) based on beamforming in a sub-Terahertz band for smart radio environments (SREs). We briefly review research on SREs with reconfigurable intelligent surfaces (RISs), and describe requirements and key features of 6G with a sub-Terahertz band. After that, we explain propagation characteristics of sub-Terahertz band radio waves. Important feature is that the number of multipath components is small in a sub-Terahertz band in indoor office environments. This leads to an IRS control method based on beamforming because the number of radio waves out of the optimum beam is very small and power that is not used for transmission from the IRS to user equipment (UE) is little in the environments. We use beams generated by a Butler matrix or a DFT matrix. In simulations, we compare the received power at a UE with that of the upper bound value. Simulation results show that the proposed method reveals good performance in the sense that the received power is not so lower than the upper bound value.

Direction of arrival (DOA) estimation is an antenna array signal processing technique used in, for instance, radar and sonar systems, source localization, and channel state information retrieval. As new applications and use cases appear with the development of next generation mobile communications systems, DOA estimation performance must be continually increased in order to support the nonstop growing demand for wireless technologies. In previous works, we verified that a deep neural network (DNN) trained offline is a strong candidate tool with the promise of achieving great on-grid DOA estimation performance, even compared to traditional algorithms. In this paper, we propose new techniques for further DOA estimation accuracy enhancement incorporating signal-to-noise ratio (SNR) prediction and an end-to-end DOA estimation system, which consists of three components: source number estimator, DOA angular spectrum grid estimator, and DOA detector. Here, we expand the performance of the DOA detector and angular spectrum estimator, and present a new solution for source number estimation based on DNN with very simple design. The proposed DNN system applied with said enhancement techniques has shown great estimation performance regarding the success rate metric for the case of two radio wave sources although not fully satisfactory results are obtained for the case of three sources.

Much attention has recently been paid to direction of arrival (DOA) estimation using compressed sensing (CS) techniques, which are sparse signal reconstruction methods. In our previous study, we developed a method for estimating the DOAs of multi-band signals that uses CS processing and that is based on the assumption that incident signals have the same complex amplitudes in all the bands. That method has a higher probability of correct estimation than a single-band DOA estimation method using CS. In this paper, we propose novel DOA estimation methods for multi-band signals with frequency characteristics using the Khatri-Rao product. First, we formulate a method that can estimate DOAs of multi-band signals whose phases alone have frequency dependence. Second, we extend the scheme in such a way that we can estimate DOAs of multi-band signals whose amplitudes and phases both depend on frequency. Finally, we evaluate the performance of the proposed methods through computer simulations and reveal the improvement in estimation performance.

In a frequency-selective multiple-input multiple-output (MIMO) channel, the optimum transmission is achieved by beamforming with eigenvectors obtained at each discrete frequency point, i.e., an extension of eigenbeam-space division multiplexing (E-SDM). However, the calculation load of eigenvalue decomposition at the transmitter increases in proportion to the number of frequency points. In addition, frequency-independent eigenvectors increase the delay spread of the effective channel observed at the receiver. In this paper, we propose a pseudo eigenvector scheme for the purpose of mitigating the calculation load and maintaining frequency continuity (or decreasing the delay spread). First, we demonstrate that pseudo eigenvectors reduce the delay spread of the effective channels with low computational complexity. Next, the practical performance of the pseudo E-SDM (PE-SDM) transmission is evaluated. The simulation results show that PE-SDM provides almost the same or better performance compared with E-SDM when the receiver employs a time-windowing-based channel estimation available in the low delay spread cases.

In SDMA, a spatial domain interference canceller applying a multistage processing concept to the MMSE multibeam adaptive array has an attractive feature. Weak power signals strongly interfered can be detected in the succeeded stages after removing other strong power signals which are already detected. This idea can be enhanced to the reference timing estimation required in the MMSE algorithm. In this paper, the spatial domain interference canceller introducing multistage timing estimation is proposed and its performance is evaluated by computer simulations. The results show that the timing estimation performance highly improved.

This paper investigates the dominant impact on the interference rejection combining (IRC) receiver due to the downlink reference signal (RS) based covariance matrix estimation scheme. When the transmission modes using the cell-specific RS (CRS) in LTE/LTE-Advanced are assumed, the property of the non-precoded CRS is different from that of the data signals. This difference poses two problems to the IRC receiver. First, it results in different levels of accuracy for the RS based covariance matrix estimation. Second, assuming the case where the CRS from the interfering cell collides with the desired data signals of the serving cell, the IRC receiver cannot perfectly suppress this CRS interference. The results of simulations assuming two transmitter and receiver antenna branches show that the impact of the CRS-to-CRS collision among cells is greater than that for the CRS interference on the desired data signals especially in closed-loop multiple-input multiple-output (MIMO) systems, from the viewpoint of the output signal-to-interference-plus-noise power ratio (SINR). However, the IRC receiver improves the user throughput by more than 20% compared to the conventional maximal ratio combining (MRC) receiver under the simulation assumptions made in this paper even when the CRS-to-CRS collision is assumed. Furthermore, the results verify the observations made in regard to the impact of inter-cell interference of the CRS for various average received signal-to-noise power ratio (SNR) and signal-to-interference power ratio (SIR) environments.

Space-Time Turbo code is an effective method for the enhancement of link capacity and maximizing the link-budget by balancing the coding gain obtained via Turbo codes and the diversity gain obtained through multiple antenna transmission. A study on an antenna selection scheme for Space-Time Turbo code for OFDM systems is presented in this paper. In the proposed method, the systematic bits and the punctured parity bits are sent from the selected antenna for each sub-carrier, while data transmission is suspended from the antenna experiencing poor channel conditions at the receiver. Simulation results show that the proposed method yields a 2.2 dB gain in the required TxEb/N0 relative to the conventional method, and makes the channel estimation accuracy more robust. Moreover, the proposed method reduces transmission power by about 4 dB compared to the conventional method.

Detecting signals in a very large multiple-input multiple-output (MIMO) system requires high complexy of implementation. Thus, belief propagation based detection has been studied recently because of its low complexity. When the transmitted signal sequence is encoded using a channel code decodable by a factor-graph-based algorithm, MIMO signal detection and channel decoding can be combined in a single factor graph. In this paper, a low density parity check (LDPC) coded MIMO system is considered, and two types of factor graphs: bipartite and tripartite graphs are compared. The former updates the log-likelihood-ratio (LLR) values at MIMO detection and parity checking simultaneously. On the other hand, the latter performs the updates alternatively. Simulation results show that the tripartite graph achieves faster convergence and slightly better bit error rate performance. In addition, it is confirmed that the LLR damping in LDPC decoding is important for a stable convergence.

Although multi-user multiple-input multiple-output (MI-MO) systems provide high data rate transmission, they may suffer from interference. Block diagonalization and eigenbeam-space division multiplexing (E-SDM) can suppress interference. The transmitter needs to determine beamforming weights from channel state information (CSI) to use these techniques. However, MIMO channels change in time-varying environments during the time intervals between when transmission parameters are determined and actual MIMO transmission occurs. The outdated CSI causes interference and seriously degrades the quality of transmission. Channel prediction schemes have been developed to mitigate the effects of outdated CSI. We evaluated the accuracy of prediction of autoregressive (AR)-model-based prediction and Lagrange extrapolation in the presence of channel estimation error. We found that Lagrange extrapolation was easy to implement and that it provided performance comparable to that obtained with the AR-model-based technique.

Massive MIMO is known as a promising technology for multiuser multiplexing in the fifth generation mobile communication system to accommodate the rapidly-increasing traffic. It has a large number of antenna elements and thus provides very sharp beams. As seen in hybrid beamforming, there have already been many papers on the concatenation of two precoders (beamformers). The inner precoder, i.e., a multi-beam former, performs a linear transformation between the element space and the beam space. The outer precoder forms nulls in the limited beam space spanned by selected beams to suppress the inter-user interference. In this two-step precoder, the beam shape is expected to determine the system performance. In this paper, we evaluate the achievable throughput performance for different beam-shaping schemes: a discrete Fourier transform (DFT) beam, Chebyshev weighted beams, and Taylor weighted beam. Simulations show that the DFT beam provides the best performance except the case of imperfect precoding and cell edge SNR of 30dB.

It is difficult for an adaptive array to reduce interference signals efficiently from received signals when the interference signals and desired signal are closely located. This is a problem for a spatial division multiple access (SDMA) system using the multibeam adaptive array as a multiuser detector. In this paper, we propose a space domain multistage interference canceller (SD-MIC) for the SDMA system. Its performance is evaluated by computer simulations, assuming Japanese personal handy phone system (PHS) uplink environments. The results show remarkable improvement in high spatial correlation situations.

Sparse modeling is one of the most active research areas in engineering and science. The technique provides solutions from far fewer samples exploiting sparsity, that is, the majority of the data are zero. This paper reviews sparse modeling in radio techniques. The first half of this paper introduces direction-of-arrival (DOA) estimation from signals received by multiple antennas. The estimation is carried out using compressed sensing, an effective tool for the sparse modeling, which produces solutions to an underdetermined linear system with a sparse regularization term. The DOA estimation performance is compared among three compressed sensing algorithms. The second half reviews channel state information (CSI) acquisitions in multiple-input multiple-output (MIMO) systems. In time-varying environments, CSI estimated with pilot symbols may be outdated at the actual transmission time. We describe CSI prediction based on sparse DOA estimation, and show excellent precoding performance when using the CSI prediction. The other topic in the second half is sparse Bayesian learning (SBL)-based channel estimation. A base station (BS) has many antennas in a massive MIMO system. A major obstacle for using the massive MIMO system in frequency-division duplex mode is an overhead for downlink CSI acquisition because we need to send many pilot symbols from the BS and to get the feedback from user equipment. An SBL-based channel estimation method can mitigate this issue. In this paper, we describe the outline of the method, and show that the technique can reduce the downlink pilot symbols.

Frequency-domain equalization (FDE) has been studied for suppressing inter-symbol interference (ISI) due to frequency selective fading in single carrier systems. When a high-mobility terminal is assumed in the system, channel transition within an FDE block cannot be ignored. The ISI reduction performance of FDE degrades since the cyclicity of the channel matrix is lost. To solve this problem, a method of dividing the received data block into multiple subblocks has been proposed, where pseudo cyclic prefix (CP) processing is introduced to realize periodicity in each subblock. In this method, the performance is degraded by the inherently-inaccurate pseudo CP. In this paper, we study the application of frequency-domain turbo equalization (FDTE) to subblock processing for improving the accuracy of pseudo CP. The simulation results show that FDTE with subblock processing yields remarkable performance improvements.

A sub-Terahertz band is envisioned to play a great role in 6G to achieve extreme high data-rate communication. In addition to very wide band transmission, we need spatial multiplexing using a hybrid MIMO system. A recently presented paper, however, reveals that the number of observed multipath components in a sub-Terahertz band is very few in indoor environments. A channel with few multipath components is called sparse. The number of layers (streams), i.e. multiplexing gain in a MIMO system does not exceed the number of multipaths. The sparsity may restrict the spatial multiplexing gain of sub-Terahertz systems, and the poor multiplexing gain may limit the data rate of communication systems. This paper describes fundamental considerations on sub-Terahertz MIMO spatial multiplexing in indoor environments. We examined how we should steer analog beams to multipath components to achieve higher channel capacity. Furthermore, for different beam allocation schemes, we investigated eigenvalue distributions of a channel Gram matrix, power allocation to each layer, and correlations between analog beams. Through simulation results, we have revealed that the analog beams should be steered to all the multipath components to lower correlations and to achieve higher channel capacity.

A time-reversal (TR) approach with multiple signal classification (MUSIC) provides super-resolution for detection and localization using multistatic data collected from an array antenna system. The theory of TR-MUSIC assumes that the number of antenna elements is greater than that of scatterers (targets). Furthermore, it requires many sets of frequency-domain data (snapshots) in seriously noisy environments. Unfortunately, these conditions are not practical for real environments due to the restriction of a reasonable antenna structure as well as limited measurement time. We propose an approach that treats both noise reduction and relaxation of the transceiver restriction by using a time-domain gating technique accompanied with the Fourier transform before applying the TR-MUSIC imaging algorithm. Instead of utilizing the conventional multistatic data matrix (MDM), we employ a modified MDM obtained from the gating technique. The resulting imaging functions yield more reliable images with only a few snapshots regardless of the limitation of the antenna arrays.

Ultrawide-band impulse radio (UWB-IR) technology and multiple-input multiple-output (MIMO) systems have attracted interest regarding their use in next-generation high-speed radio communication. We have studied the use of MIMO ultrawide-band (MIMO-UWB) systems to enable higher-speed radio communication. We used frequency-domain equalization based on the minimum mean square error criterion (MMSE-FDE) to reduce intersymbol interference (ISI) and co-channel interference (CCI) in MIMO-UWB systems. Because UWB systems are expected to be used for short-range wireless communication, MIMO-UWB systems will usually operate in line-of-sight (LOS) environments and direct waves will be received at the receiver side. Direct waves have high power and cause high correlations between antennas in such environments. Thus, it is thought that direct waves will adversely affect the performance of spatial filtering and equalization techniques used to enhance signal detection. To examine the feasibility of MIMO-UWB systems, we conducted MIMO-UWB system propagation measurements in LOS environments. From the measurements, we found that the arrival time of direct waves from different transmitting antennas depends on the MIMO configuration. Because we can obtain high power from the direct waves, direct wave reception is critical for maximizing transmission performance. In this paper, we present our measurement results, and propose a way to improve performance using a method of transmit (Tx) and receive (Rx) timing control. We evaluate the bit error rate (BER) performance for this form of timing control using measured channel data.

A distributed antenna system, where the antennas of a base station are spatially distributed throughout the cell, can achieve better throughput at the cell edge than a centralized antenna system. On the other hand, the peak throughput degrades in general because each remote antenna unit has only a few antennas. To achieve both high peak and cell-edge throughputs, we need to increase the total number of antennas. However, this is not easy due to the pilot resource limitation when we use frequency division duplexing. In this paper, we propose using more antennas than pilot resources. The number mismatch between antennas and signals is solved by using a connection matrix. Here, we test two types of connection matrix: signal-distributing and signal-switching. Simulation results show that the sum throughput is improved by increasing the number of antenna elements per remote antenna unit under a constraint on the same number of pilot resources.

Currently, space division multiplexing (SDM), where individual data streams are transmitted from different antennas simultaneously, is expected to be a promising technology for achieving a high data rate within a limited frequency band in a multiple-input multiple-output channel. In this paper, transmitter and receiver architectures of SDM applications are described, and performance improvement with the increase of data streams is shown referring to results of computer simulations. In addition, channel coded systems are also evaluated.

We consider space division multiplexing in a MIMO-OFDM system for high data rate transmission. Channel estimation is very important for suppressing interference and demultiplexing signals. In a wireless LAN system such as IEEE 802.11a, only a few training symbols are inserted in each subcarrier. First, we propose a channel estimation method for a MIMO-OFDM system with two training symbols per subcarrier. The basic idea is to estimate the time-domain channel responses between the transmit and receive antennas. The array response vectors for each subcarrier are calculated by applying a fast Fourier transform to them. We then can obtain the adaptive weights to cancel the interference. We show that employing training symbols having a lower condition number of the matrix used for the channel estimation improves the estimation accuracy. Furthermore, we show the bit error rate for several signal detection schemes using the above estimated channel. It is shown that an ordered successive detection based on an MMSE criterion has excellent performance, that is, it can achieve higher-speed transmissions with a lower transmit power.

A uniform circular array (UCA) is a well-known array configuration which can accomplish estimation of 360 field of view with identical accuracy. However, a UCA cannot estimate coherent signals because we cannot apply the SSP owing to the structure of UCA. Although a variety of studies on UCA in coherent multipath environments have been done, it is impossible to estimate the DOA of coherent signals with different incident polar angles. Then, we have proposed Root-MUSIC algorithm with a cylindrical array. However, the estimation performance is degraded when incident signals arrive with close polar angles. To solve this problem, in the letter, we propose to use SAGE algorithm with a cylindrical array. Here, we adopt a CLA Root-MUSIC for the initial estimation and decompose two-dimensional search to double one-dimensional search to reduce the calculation load. The results show that the proposal achieves high resolution with low complexity.