In order to utilize higher frequency bands above 6GHz, which is an important technical challenge in fifth generation mobile systems, radio propagation channel properties in a large variety of deployment scenarios should be thoroughly investigated. The authors' group has been involved in a fundamental research project aimed at investigating multiple-input-multiple-output (MIMO) transmission performance and propagation channel properties at microwave frequency above 10GHz from 2009 to 2013, and since then they have been conducting measurement and modeling for high frequency bands. This paper aims at providing comprehensive tutorial of a whole procedure of channel modeling; multi-dimensional channel sounding, propagation channel measurement, analysis, and modeling, by introducing the developed MIMO channel sounders at high frequency bands of 11 and 60GHz and presenting some measurement results in a microcell environment at 11GHz. Furthermore, this paper identifies challenges in radio propagation measurements, and discusses current/future channel modeling issues as future works.

Non-linear precoding (NLP) scheme for downlink multi-user multiple-input multiple-output (DL-MU-MIMO) transmission has received much attention as a promising technology to achieve high capacity within the limited bandwidths available to radio access systems. In order to minimize the required transmission power for DL-MU-MIMO and achieve high spectrum efficiency, Vector Perturbation (VP) was proposed as an optimal NLP scheme. Unfortunately, the original VP suffers from significant computation complexity in detecting the optimal perturbation vector from an infinite number of the candidates. To reduce the complexity with near transmission performance of VP, several recent studies investigated various efficient NLP schemes based on the concept of Tomlinson-Harashima precoding (THP) that applies successive pre-cancellation of inter-user interference (IUI) and offsets the transmission vector based on a modulo operation. In order to attain transmission performance improvement over the original THP, a previous work proposed Minimum Mean Square Error based THP (MMSE-THP) employing IUI successive pre-cancellation based on MMSE criteria. On the other hand, to improve the transmission performance of MMSE-THP, other previous works proposed Ordered MMSE-THP and Lattice-Reduction-Aided MMSE-THP (LRA MMSE-THP). This paper investigates the further transmission performance improvement of Ordered MMSE-THP and LRA MMSE-THP. This paper starts by proposing an extension of MMSE-THP employing a perturbation vector search (PVS), called PVS MMSE-THP as a novel NLP scheme, where the modulo operation is substituted by PVS and a subtraction operation from the transmit signal vector. Then, it introduces an efficient search algorithm of appropriate perturbation vector based on a depth-first branch-and-bound search for PVS MMSE-THP. Next, it also evaluates the transmission performance of PVS MMSE-THP with the appropriate perturbation vector detected by the efficient search algorithm. Computer simulations quantitatively clarify that PVS MMSE-THP achieves better transmission performance than the conventional NLP schemes. Moreover, it also clarifies that PVS MMSE-THP increases the effect of required transmission power reduction with the number of transmit antennas compared to the conventional NLP schemes.

In-band full-duplex (FD) Multiple-Input and Multiple-Output (MIMO) communication performs uplink and downlink transmission at the same time using the same frequency. In this system, the spectral efficiency is theoretically double that of conventional duplex schemes, such as Time Division Duplex (TDD) and Frequency Division Duplex (FDD). However, this system suffers interference because the uplink and downlink streams coexist within the same channel. Especially at the terminal side, it is quite difficult for the terminal to eliminate the interference signals from other terminals since it has no knowledge about the contents of the interference signals. This paper presents an inter-terminal interference suppression method between the uplink and downlink signals assuming the multi-user environment. This method uses eigen-beamforming at the transmitting terminal to direct the null to the other terminal. Since this beamforming technique reduces the degrees of freedom available, the interference suppression performance and transmitting data-rate have a trade-off relation. This study investigates the system capacity characteristics in multi-user full-duplex MIMO communication using the propagation channel information measured in an actual outdoor experiment and shows that the proposed communication scheme offers higher system capacity than the conventional scheme.

This paper proposes a novel method of reducing channel state information (CSI) feedback by using transmit antenna selection for downlink multiuser multiple input multiple output (DL-MU-MIMO) transmission in dense distributed antenna systems. It is widely known that DL-MU-MIMO transmission achieves higher total bit-rate by mitigating inter-user interference based on pre-coding techniques. The pre-coding techniques require CSI between access point (AP) and multiple users. However, overhead for CSI acquisition degrades the transmission efficiency of DL-MU-MIMO transmission. In the proposed CSI feedback reduction method, AP first selects the antenna set that maximizes the received power at each user, second it skips the sequence of CSI feedback for users whose signal to interference power ratio is larger than a threshold, and finally it performs DL-MU-MIMO transmission to multiple users by using the selected antenna set. To clarify the proposed method, we evaluate it by computer simulations in an indoor scenario. The results show that the proposed method can offer higher transmission efficiency than the conventional DL-MU-MIMO transmission with the usual CSI feedback method.

In this paper, we propose a low-complexity widely-linear minimum mean square error (WL-MMSE) signal detection based on the Chebyshev polynomials accelerated symmetric successive over relaxation (SSORcheb) algorithm for uplink (UL) over-loaded large-scale multiple-input multiple-output (MIMO) systems. The technique of utilizing Chebyshev acceleration not only speeds up the convergence rate significantly, and maximizes the data throughput, but also reduces the cost. By utilizing the random matrix theory, we present good estimates for the Chebyshev acceleration parameters of the proposed signal detection in real large-scale MIMO systems. Simulation results demonstrate that the new WL-SSORcheb-MMSE detection not only outperforms the recently proposed linear iterative detection, and the optimal polynomial expansion (PE) WL-MMSE detection, but also achieves a performance close to the exact WL-MMSE detection. Additionally, the proposed detection offers superior sum rate and bit error rate (BER) performance compared to the precision MMSE detection with substantially fewer arithmetic operations in a short coherence time. Therefore, the proposed detection can satisfy the high-density and high-mobility requirements of some of the emerging wireless networks, such as, the high-mobility Internet of Things (IoT) networks.

In this paper, we propose a novel error recovery method for massive multiple-input multiple-output (MIMO) signal detection, which improves an estimate of transmitted signals by taking advantage of the sparsity and the discreteness of the error signal. We firstly formulate the error recovery problem as the maximum a posteriori (MAP) estimation and then relax the MAP estimation into a convex optimization problem, which reconstructs a discrete-valued sparse vector from its linear measurements. By using the restricted isometry property (RIP), we also provide a theoretical upper bound of the size of the reconstruction error with the optimization problem. Simulation results show that the proposed error recovery method has better bit error rate (BER) performance than that of the conventional error recovery method.

In this paper, we propose a new spatial modulation (SM) scheme based on quaternary quasi-orthogonal sequences (Q-QOSs), referred to as Q-QOS-SM. First, the conventional SM and generalized-SM (GSM) schemes are reinterpreted as a new transmission scheme based on a spatial modulation matrix (SMM), whose column indices are used for the mapping of spatial-information bits unlike the conventional ones. Next, by adopting the SMM comprising the Q-QOSs, the proposed Q-QOS-SM that guarantees twice the number of spatial bits at a transmitter compared with the SM with a constraint of transmit antennas, is designed. From the computer-simulation results, the Q-QOS-SM is shown to achieve a greatly improved throughput compared with the conventional SM and GSM schemes, especially, for a large number of the receive antennas. This finding is mainly because the new scheme offers a much higher minimum Euclidean distance than the other schemes.

In this letter, a switching detection scheme based on a channel condition number for the MIMO-OFDM system is proposed. The switching algorithm operates by selecting one of three detection schemes of QRD-M, LR-aided MMSE-DFE, and LR-aided MMSE. The switching detection uses the threshold based on the switching algorithm according to the channel condition number. From the simulation results, the proposed detection scheme shows error detection performance and computational complexity in accordance with the threshold for switching detection.

This letter considers the robust Tomlinson-Harashima Precoding(THP) transceiver design for Multiple-Input Multiple-Output (MIMO) interference channel (IC). Assuming bounded channel state information (CSI) error, we deal with the optimization for minimizing the worst case per-user mean square error (MSE) and sum MSE. We present an approximate approach to derive the upper bound of the constraint leading to less semidefinite. Then the alternate approach is adopted to update the receiver matrix by solving second-order-cone programming (SOCP), and update the transmitter matrix and feedback matrix by solving semidefinite program (SDP), respectively. Simulation results show that the proposed method achieves similar performance of the S-procedure method, whereas the computation complexity is reduced significantly, especially for the system with large number of transmit antennas.

High-resolution image and video communication in home networks is highly expected to proliferate with the spread of Wi-Fi devices and the introduction of multiple-input multiple-output (MIMO) systems. This paper proposes a joint transmission and coding scheme for broadcasting high-resolution video streams over multiuser MIMO systems with an eigenbeam-space division multiplexing (E-SDM) technique. Scalable video coding makes it possible to produce the code stream comprised of multiple layers having unequal contribution to image quality. The proposed scheme jointly assigns the data of scalable code streams to subcarriers and spatial streams based on their signal-to-noise ratio (SNR) values in order to transmit visually important data with high reliability. Simulation results show that the proposed scheme surpasses the conventional unequal power allocation (UPA) approach in terms of both peak signal-to-noise ratio (PSNR) of received images and correct decoding probability. PSNR performance of the proposed scheme exceeds 35dB with the probability of over 95% when received SNR is higher than 6dB. The improvement in average PSNR by the proposed scheme compared to the conventional UPA comes up to approx. 20dB at received SNR of 6dB. Furthermore, correct decoding probability reaches 95% when received SNR is greater than 4dB.

Massive MIMO (mMIMO) is a promising technology for smart multimedia and wireless communication fields. In this paper, we investigate pilot allocation problem in two-tier time division duplex (TDD) heterogeneous network (HetNet) with mMIMO. First, we propose a new pilot allocation scheme for maximizing ergodic downlink sum rate of macro users (MUs) and small cell users (SUs), where the uplink pilot overhead and cross-tier interference are jointly considered. Then, we theoretically analyze the formulated problem and propose a low complexity one-dimensional search algorithm to obtain the optimum pilot allocation. In addition, we propose two suboptimal pilot allocation algorithms to simplify the computational process and improve SUs' fairness, respectively. Finally, simulation results show that the performance of the proposed scheme outperforms that of the traditional schemes.

This paper proposes a new methodology to design optimal antennas for MIMO (Multi-Input Multi-Output) communication systems by using spherical mode expansion. Given spatial channel properties of a MIMO channel, such as the angular profile at both sides, the optimal MIMO antennas should provide the largest channel capacity with a constraint of the limited implementation space (volume). In designing a conventional MIMO antenna, first the antenna structure (current distribution) is determined, second antenna directivity is calculated based on the current distribution, and thirdly MIMO channel capacity is calculated by using given angular profiles and obtained antenna directivity. This process is repeated by adjusting the antenna structure until the performance satisfies a predefined threshold. To the contrary, this paper solves the optimization problem analytically and finally gives near optimal antenna structure (current distribution) without any greedy search. In the proposed process, first the optimal directivity of MIMO antennas is derived by applying spherical mode expansion to the angular profiles, and second a far-near field conversion is applied on the derived optimal directivity to achieve near optimal current distributions on a limited surface. The effectiveness of the proposed design methodology is validated via numerical calculation of MIMO channel capacity as in the conventional design method while giving near optimal current distribution with constraint of an antenna structure derived from proposed methodology.

In order to tackle rapidly increasing traffic, dramatic performance enhancements in radio access technologies (RATs) are required for fifth-generation (5G) mobile communication system. In 5G, small/semi-macro cells using Massive MIMO (M-MIMO) with much wider bandwidth in higher frequency bands are overlaid on macro cell with existing frequency band. Moreover, high density deployment of small/semi-macro cell is expected to improve areal capacity. However, in low SHF band (below 6GHz), antenna array size of M-MIMO is large so that it cannot be installed on some environments. Therefore, to improve system throughput on various use cases in 5G, we have proposed distributed Massive MIMO (DM-MIMO). DM-MIMO coordinates lots of distributed transmission points (TPs) that are located in ultra-high density (UHD). Furthermore, DM-MIMO uses various numbers of antenna elements for each TP. In addition, DM-MIMO with UHD-TPs can create user-centric virtual cells corresponding to user mobility, and design of flexible antenna deployment for DM-MIMO is applicable to various use cases. Then, some key parameters such as the number of the distributed TPs, the number of antenna elements for each TP, and proper distance between TPs, should be determined. This paper presents such parameters for 5G DM-MIMO with flexible antenna deployment under fixed total transmission power and constant total number of antenna elements. Computer simulations show that DM-MIMO can achieve more than 1.9 times higher system throughput than an M-MIMO system using 128 antenna elements.

A 15GHz-band 4-channel transmit/receive RF core-chip is presented for high SHF wide-band massive MIMO in 5G. In order to realize small RF frontend for 5G base stations, both 6bit phase shifters (PS) and 0.25 dB resolution variable gain amplifiers (VGA) are integrated in TX and RX paths of 4-channels on the chip. A PS calibration technique is applied to compensate the error of 6bit PS caused by process variations. A common gate current steering topology with tail current control is used for VGA to enhance the gain control accuracy. The 15GHz-band RF core-chip fabricated in 65 nm CMOS process achieved phase control error of 1.9deg. rms., and amplitude control error of 0.23 dB. rms.

In this paper, we present the roles played by millimeter-waves in the realization of an Internet of Things (IoT) society. Millimeter-waves are becoming essential frequency resources, enabling ultra-high-speed wireless networks supporting massive data traffic and high-resolution sensor devices. Multiple antenna technologies such as phased arrays, sector antennas, and MIMO signal processing are key technologies for putting these into practical use. In this paper, various examples of integration of multi-antenna systems are shown, as well as demonstration on 60GHz-band millimeter-wave wireless access and 79GHz-band high-resolution radar. We also propose applications to ITS for an IoT society, combining millimeter-wave wireless access and radar sensors, and discuss technical issues to be solved in the future.

The Long Term Evolution (LTE) of mobile communication standard was designed by the 3rd generation partnership project (3GPP) to serve the requirements. Nowadays, the combining of the orthogonal frequency division multiplexing (OFDM) and the multiple input multiple output (MIMO) is supported in LTE system. The MIMO-OFDM is considered to improve data rate and channel capacity without additional bandwidth. Because the receivers get all transmission signals from all transmitters at the same time, many detection schemes have been developed for accurate estimation and low complexity. Among the detection schemes, the QR decomposition with M algorithm (QRD-M) achieves optimal error performance with low complexity. Nevertheless, the conventional QRD-M has high complexity for implementation. To overcome the problem, this letter proposes the low complexity QRD-M detection scheme in MIMO-OFDM systems. The proposed scheme has two elements which decide layer value and the limited candidates. The two elements are defined by the number of transmit antennas and the cardinality of modulation set respectively. From simulation results, the proposed scheme has the same error performance with the conventional QRD-M and very lower complexity than the conventional QRD-M.

A novel generalized side-information cancellation (GSIC) precoder is proposed for multiuser multi-input multi-output (MIMO) downlink systems with channel state information at the transmitter. The proposed transceiver involves the following stages. First, a minimum mean square error (MMSE) based channel inversion (MMSE-CI) technique is utilized to suppress multiuser broadcast interference. By using a GSIC technique, it can further reduce the residual multiuser interference and the noise induced by MMSE-CI preprocessing. Next, with a singular value decomposition method, the spatial stream interference of each user is suppressed by the pre-processing and post-processing eigenvector matrices. Finally, the proposed precoder can be extended to joint water filling and diagonal loading methods for performance enhancement. For the correlated MIMO channels, signal subspace and antenna selection methods, incorporating the proposed GSIC precoder, are further designed to maximize the sum rate performance. Simulation results show that the proposed GSIC precoder outperforms the conventional precoders. Besides, simulation results confirm that the proposed GSIC precoder with water filling, diagonal loading, and signal subspace techniques exhibits excellent performance.

The breadth-first tree searching (BFTS) detection algorithm such as the QR decomposition with M algorithm (QRD-M) which is the generally K-best detection algorithm is suboptimal, but has high complexity. In this letter, the K-best BFTS detection algorithm having reduced complexity is proposed. The proposed detection algorithm calculates the channel condition to decide the thresholds for regulating complexity and performance and from the simulation results, it has good error performance with very low complexity.

In order to satisfy the very high traffic demand in crowded hotspot areas and realize adequate security in future fifth-generation networks, this paper studies physical-layer security in the downlink of a two-tier ultra dense heterogeneous network, where a ubiquitous array formed by ultra dense deployed small-cells surrounds a macrocell base station. In this paper, the locations of legitimate users and eavesdroppers are drawn from Poisson point processes. Then, the cumulative distribution functions of the receive signal-to-interference-plus-noise ratio for legitimate users and eavesdroppers are derived. Further, the average secrecy rate and secrecy coverage probability for each tier as well as for the whole network are investigated. Finally, we analyze the influences on secrecy performance caused by eavesdropper density, transmit power allocation ratio, antenna number allocation ratio, and association area radius.

In order to meet various requirements for the 5th generation mobile communication, a high SHF wideband massive-MIMO system has been widely studied which offers wide system bandwidth and high spectral efficiency. A hybrid beamforming configuration which combines analog beamforming by APAA (Active Phased Array Antenna) and digital MIMO signal processing is one of the promising approaches for reducing the complexity and power consumption of the high SHF wideband massive-MIMO system. In order to realize the hybrid beamforming configuration in high SHF band, small size, low power consumption and precise beam forming over the wide-band frequency range are strongly required for RF frontend which constitutes analog beam former. In this paper, a compact RF frontend module for high SHF wideband 5G small cell base station is proposed. This RF frontend module is prototyped. Various key components of the RF frontend module are fabricated in 15GHz band, and measured results show that high RF performances are able to meet the requirements of RF frontend.