This paper proposes a novel MIMO system that introduces a heterogeneous stream (HTS) scheme and a blind signal detection method for mobile radio communications. The HTS scheme utilizes different modulation or coding methods for different MIMO streams, and the blind detection method requires no training sequences for signal separation, detection, and channel estimation. The HTS scheme can remove the ambiguity in identifying separated streams without unique words that are necessary in conventional MIMO blind detection. More specifically, two examples of HTS are considered: modulation type HTS (MHTS) and timing-offset type HTS (THTS). MHTS, which utilizes different modulation constellations with the same bandwidth for different streams, has been previously investigated. This paper proposes THTS which utilizes different transmission timing with the same modulation. THTS can make the blind detection more robust and effective with fractional sampling. The blind joint processing of detection and channel estimation performs adaptive blind MIMO-MLSE and is derived from an adaptive blind MLSE equalizer that employs the recursive channel estimation with the Moore-Penrose generalized inverse. Computer simulations show that the proposed system can achieve superior BER performance with Eb/N0 degradation of 1 dB in THTS and 2.5 dB in MHTS compared with the ideal maximum likelihood detection.

In March 2020, the 5th generation mobile communication system (5G) was launched in Japan. Frequency bands of 3.7GHz, 4.5GHz and 28GHz were allocated for 5G services, and the 5G use cases fall into three broad categories: Enhanced Mobile Broadband (eMBB), Massive Machine Type Communication (mMTC) and Ultra-Reliable Low Latency Communication (URLLC). The use cases and services that take advantage of the characteristics of each category are expected to be put to practical use, and experiments of practical use are underway. This paper introduces and demonstrates a touchless gate that can identify, authenticate and allow passage through the gate by using these features and 5G beam tracking to estimate location by taking advantage of the low latency of 5G and the straightness of the 28GHz band radio wave and its resistance to spreading. Since position estimation error due to reflected waves and other factors has been a problem, we implement an algorithm that tracks the beam and estimates the user's line of movement, and by using an infrared sensor, we made it possible to identify the gate through which the user passes with high probability. We confirmed that the 5G touchless gate is feasible for gate passage. In addition, we demonstrate that a new service based on high-speed high-capacity communication is possible at gate passage by taking advantage of the wide bandwidth of the 28GHz band. Furthermore, as a use case study of the 5G touchless gate, we conducted a joint experiment with an airline company.

This paper proposes a new blind adaptive MLSE equalizer for frequency selective mobile radio channels. The proposed equalizer performs channel estimation for each survivor path of the Viterbi algorithm (VA), and restricts the number of symbol candidates for the channel estimation in order to reduce prohibitive complexity. In such channel estimation, autocorrelation matrices of the symbol candidates are likely to become singular, which increases the estimation error. To cope with the singularity, the proposed equalizer employs a recursive channel estimation algorithm using the Moore-Penrose generalized inverse of the autocorrelation matrix. As another problem, the blind channel estimation can yield plural optimal estimates of a channel impulse response, and the ambiguity of the estimates degrades the BER performance. To avoid this ambiguity, the proposed equalizer is enhanced so that it can take advantage of the fractional sampling. The enhanced equalizer performs symbol-spaced channel estimation for each fractional sampling phase. This equalizer combines separate channel estimation errors, and provides the sum to the VA processor as the branch metric, which tremendously reduces the probability that a correct estimate turns into a false one. Computer simulation demonstrates the effectiveness of the proposed equalizers in the frequency selective fading channels.

This paper shows accuracy of using azimuth-variable path-loss fitting in white-space (WS) boundary-estimation. We perform experiments to evaluate this method, and demonstrate that the required number of sensors can be significantly reduced. We have proposed a WS boundary-estimation framework that utilizes sensors to not only obtain spectrum sensing data, but also to estimate the boundaries of the incumbent radio system (IRS) coverage. The framework utilizes the transmitter position information and pathloss fitting. The pathloss fitting describes the IRS coverage by approximating the well-known pathloss prediction formula from the received signal power data, which is measured using sensors, and sensor-transmitter separation distances. To enhance its accuracy, we have further proposed a pathloss-fitting method that employs azimuth variables to reflect the azimuth dependency of the IRS coverage, including the antenna directivity of the transmitter and propagation characteristics.

5G service has been launched in various countries, and research for the beyond 5G is already underway actively around the world. In beyond 5G, it is expected to expand the various capabilities of communication technologies to cover further wide use cases from 5G. As a candidate elemental technology, cell free massive MIMO has been widely researched and shown its potential to enhance the capabilities from various aspects. However, for deploying this technology in reality, there are still many technical issues such as a cost of distributing antenna and installing fronthaul, and also the scalability aspects. This paper surveys research trends of cell free massive MIMO, especially focusing on the deployment challenges with an introduction to our specific related research activities including some numerical examples.