This paper proposes a novel channel estimation method for iterative equalization in MIMO systems. The proposed method incorporates co-channel interference (CCI) cancellation in the channel estimator and the channel estimation is successively performed with respect to each stream. Accuracy of channel estimation holds the key to be successfully converged the iterative equalization and decoding process. Although the channel estimates can be re-estimated by means of LS (Least Square) channel estimation using tentative decisions obtained in the iterative process, its performance is severely limited in a MIMO system because of erroneous decisions and ill-conditioned channel estimation matrix. The proposed method can suppress the above effects by means of CCI cancellation and successive channel estimation. Computer simulation confirms that the proposed channel estimation method can accurately estimate the channel, and the receiver with iterative equalization and the proposed method achieves excellent decoding performance in a MIMO-SM system.

The MIMO system can meet the growing demand for higher capacity in wireless communication fields. So far, the authors have reported that, based on channel measurements, uncoded performance of narrowband MIMO spatial multiplexing in indoor line-of-sight (LOS) environments generally outperforms that in non-LOS (NLOS) ones under the same transmit power condition. In space-frequency coded MIMO-OFDM spatial multiplexing, however, we cannot expect high space-frequency diversity gain in LOS environments because of high fading correlations and low frequency selectivity of channels so that the performance may degrade unlike uncoded cases. In this letter, we present the practical performance of coded MIMO-OFDM spatial multiplexing based on indoor channel measurements. The results show that an LOS environment tends to provide lower space-frequency diversity effect whereas the MIMO-OFDM spatial multiplexing performance is still better in the environment compared with an NLOS environment.

An adaptive array has been proposed as a canceller for both inter-symbol interference (ISI) and co-channel interference (CCI). However, it has no path-diversity gain since it selects just one signal correlated to the reference signal. In this paper, a novel interference canceller having sufficient path-diversity gain is proposed. The canceller is characterized by the combined configuration of an adaptive array and an equalizer. In the proposed system, a pre-selecting adaptive array is installed first. By employing a specific training sequence and sampling timing at the receiver during the training period, the perfect correlation between the "desired signal" and "short delayed" is achieved. Therefore, the pre-selecting adaptive array can extract the desired and ISI signals simultaneously, and the cascaded adaptive equalizer can provide the path-diversity gain without degradation by interference. The proposed system achieves a simple configuration and robustness against both ISI and CCI with a sufficient path diversity gain. In computer simulations, average BER characteristics of the proposed system were evaluated in a quasi-static Rayleigh fading channel. The simulation results showed that the system can reduce both long-delayed ISI and CCI efficiently, and that the expected path diversity gain is obtained even with strong CCI. They also showed that the degradation is not so serious when the number of antenna elements is less than that of incoming signals.

Direction of arrival (DOA) estimation of wireless signals is demanded in many applications. In addition to classical methods such as MUSIC and ESPRIT, non-linear algorithms such as compressed sensing have become common subjects of study recently. Deep learning or machine learning is also known as a non-linear algorithm and has been applied in various fields. Generally, DOA estimation using deep learning is classified as on-grid estimation. A major problem of on-grid estimation is that the accuracy may be degraded when the DOA is near the boundary. To reduce such estimation errors, we propose a method of combining two DNNs whose grids are offset by one half of the grid size. Simulation results show that our proposal outperforms MUSIC which is a typical off-grid estimation method. Furthermore, it is shown that the DNN specially trained for a close DOA case achieves very high accuracy for that case compared with MUSIC.

Frequency-selective fading due to multipath propagation is serious hindrance in high-speed TDMA mobile communications. An adaptive antenna has been proposed to reduce the frequency-selective fading and realize path-diversity. This paper presents a criterion which selects multipath signals and weighting factors for combining them. First, we describe a selection criterion which chooses the multipath signals for the path-diversity. We propose a ratio of signal power to error power for the criterion. Furthermore, we propose weighting factors which realize approximately the maximal ratio combining. Computer simulation results show that the proposed selection criterion and weighting factors reveal excellent performance.

In this paper, the performance of multiuser MIMO E-SDM systems in downlink transmission is evaluated in both uncorrelated and correlated time-varying fading environments. In the ideal case, using the block diagonalization scheme, inter-user interference can be completely eliminated at each user; and using the E-SDM technique for each user, optimal resource allocation can be achieved, and spatially orthogonal substreams can be obtained. Therefore, a combination of the block diagonalization scheme and the E-SDM technique applied to multiuser MIMO systems gives very good results. In realistic environments, however, due to the dynamic nature of the channel and processing delay at both the transmitter and the receiver, the channel change during the delay may cause inter-user interference even if the BD scheme is used. In addition, the change may also result in large inter-substream interference and prevent optimal resource allocation from being achieved. As a result, system performance may be degraded seriously. To overcome the problem, we propose a method of channel extrapolation to compensate for the channel change. Applying our proposed method, simulation results show that much better system performance can be obtained than the conventional case. Moreover, it also shows that the system performance in the correlated fading environments is much dependent on the antenna configuration and the angle spread from the base station to scatterers.

Direction of arrival (DOA) estimation of wireless signals has a long history but is still being investigated to improve the estimation accuracy. Non-linear algorithms such as compressed sensing are now applied to DOA estimation and achieve very high performance. If the large computational loads of compressed sensing algorithms are acceptable, it may be possible to apply a deep neural network (DNN) to DOA estimation. In this paper, we verify on-grid DOA estimation capability of the DNN under a simple estimation situation and discuss the effect of training data on DNN design. Simulations show that SNR of the training data strongly affects the performance and that the random SNR data is suitable for configuring the general-purpose DNN. The obtained DNN provides reasonably high performance, and it is shown that the DNN trained using the training data restricted to close DOA situations provides very high performance for the close DOA cases.

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.

Research in smart antenna technology has progressed over the past few years and is gradually reaching the phase of practical use. We have developed a smart antenna test bed for wireless local area network (LAN) that is based on the IEEE802.11b. The objective is to improve anti-multipath fading performance and expand communication distance. Using this test bed, we carried out field tests in two environment. One environment is an office in an non line of sight (NLOS), and another environment is an outdoor in a line of sight (LOS). In this paper, we explain the outline of the test bed, the measurement method, and present the results of the field tests. In the office environment, we measured the performance of each set with a different number of antenna elements. The results show that the dead-spots where communication becomes impossible disappear if the number of antenna elements is more than or equal to two. In addition, a greater number of elements indicates better performance. The total average throughput is 1.6 times as efficient when two elements are used, and 1.9 times when four elements are used. Cold spots where the throughput is slower than 1 Mbps are reduced by 80-90%. In the outdoor LOS environment field test, it is shown that by using four-element smart antenna for both transmitter and receiver, the communication distance reached 1km with an average throughput of 4 Mbps. These results prove that the smart antenna drastically improves the performance of a wireless LAN system, i.e. the IEEE802.11b.

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.

This paper proposes using an adaptive array in a base station for signal reception and transmission in order to increase the spectral efficiency without decreasing the cell radius. The adaptive array controls the directivity pattern of the base station to reduce co-channel interference during reception; the same array pattern is applied during transmission to prevent unnecessary illumination. Computer simulation results show that the cluster size can be reduced to one with time division duplexing (TDD), indicating that we can reuse the same frequency group at all cells. Thus, the improvement in spectral efficiency is as much as 16 fold that of an omni-antenna. Moreover, load sharing, which is expected to improve the channel utilization for unbalanced load situations, is available by cell overlapping. Frequency division duplexing (FDD) requires a weight adjust function to be applied for transmission since the difference in frequency between signal reception and transmission causes null positioning error. However, simple LMS-adjusting can provide a cluster size of one as well as cell overlapping when the frequency deference is 5%.

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.

In high-speed TDMA mobile communications, frequency-selective fading is a serious problem because a delay time difference between multipath signals is large in comparison with symbol duration. We have proposed a spatial-domain RAKE receiver using a multibeam adaptive antenna to reduce frequency-selective fading and to realize path-diversity. The multibeam adaptive antenna resolves multipath signals in the spatial domain, and combines array outputs. In this paper, we propose the application of MUSIC algorithm to estimation of the time delays of multipath signals to make the incident signals coincide with a common reference signal. Because the MUSIC algorithm can estimate the time delays accurately, the BER performance of the proposed scheme is improved. Furthermore, we propose weighting factors which easily realize the maximal-ratio combining.

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.

Many carriers are introducing multi-media services to satisfy customer demands for these services. In order to provide such services, carrier must increase their system capacity. It is well known that space division multiple access (SDMA) improves system capacity and is compatible with existing access systems. In order to evaluate the performance of SDMA, we developed an SDMA test bed. The test bed maintains the personal handy phone systems (PHS). The PHS adopts time division multiple access (TDMA). Aiming to compare the performance of SDMA and TDMA using the same analog hardware, the SDMA test bed employs a software-defined radio (SDR) technique. This paper shows the outline and performance of the test bed. The results of laboratory tests indicate that the bit error rate (BER) of the test bed operated in the SDMA mode at under 10-3 when the carrier-tointerference ratio (CIR) was larger than approximately -22 dB. Antenna patterns measured in an anechoic chamber show that the SDMA test bed produces correct antenna patterns when there are three desired signals and one interference signal. The results of the four field tests confirm that the test bed operated while two-multiplex SDMA mode doubled of the traffic and decreased the interference level as compared with the TDMA mode. Furthermore, the test bed operated while threemultiplex SDMA mode improves the traffic about 2.4 to 2.7 times. The SDMA test bed decreased the impact of the adjusted TDMA base station (BS). Therefore, we confirmed that the SDMA improves system capacity without any degradation.