The concept of massive multiple input multiple output (MIMO) has recently been proposed. It has been reported that using linear or planar arrays to implement massive MIMO yields narrow beams that can mitigate the interference signal even if interference cancellation techniques such as zero forcing (ZF) are not employed. In this work, we investigate the interference reduction performance achieved by circular array implemented massive MIMO in a real micro cell environment. The channel state information (CSI) is obtained by using a wideband channel sounder with cylindrical 96-element array in the 2-GHz band in an urban area. Circular arrays have much larger beamwidth and sidelobe level than linear arrays. In this paper, when considering the cylindrical array, the interference reduction performance between ZF and maximum ratio combining is compared when one desired user exists in the micro cell while the interference user moves around the adjacent cell. We show that ZF is essential for reducing the interference from the adjacent cell in the circular array based massive MIMO. The required number of antennas in the vertical and horizontal planes for the interference reduction is evaluated, in order to simplify the burden of signal processing for the ZF algorithm in massive MIMO. Because there are elements with low signal to noise power ratio (SNR) when considering cylindrical 96-element array, it is shown that the degradation of the signal to noise plus interference power ratio (SINR) when the number of antennas is reduced is smaller than that by ideal antenna gain reduction with a linear array. Moreover, we show that the appropriate antennas should be selected when a limited number of antennas is assumed, because the dominant waves arrive from certain specific directions.

The fifth generation (5G) system using millimeter waves is considered for application to high traffic areas with a dense population of pedestrians. In such an environment, the effects of shadowing and scattering of radio waves by human bodies (HBs) on propagation channels cannot be ignored. In this paper, we clarify based on measurement the characteristics of waves scattered by the HB for typical non-line-of-sight scenarios in street canyon environments. In these scenarios, there are street intersections with pedestrians, and the angles that are formed by the transmission point, HB, and reception point are nearly equal to 90 degrees. We use a wide-band channel sounder for the 67-GHz band with a 1-GHz bandwidth and horn antennas in the measurements. The distance parameter between antennas and the HB is changed in the measurements. Moreover, the direction of the HB is changed from 0 to 360 degrees. The evaluation results show that the radar cross section (RCS) of the HB fluctuates randomly over the range of approximately 20dB. Moreover, the distribution of the RCS of the HB is a Gaussian distribution with a mean value of -9.4dBsm and the standard deviation of 4.2dBsm.

In this paper, we propose a simple model for estimating the effects of human body shadowing (HBS) in high frequency bands. The model includes two factors: the shadowing width (SW), which is the width of the area with shadowing loss values greater than 0dB, and the median shadowing loss value (MSLV), which is obtained by taking the median of the shadowing loss values within the SW. These factors are determined by formulas using parameters, i.e. frequency, distance between the base station (BS) and human body, distance between the terminal and human body, BS antenna height, and direction of the human body. To obtain the formulas, a method for calculating the effects of HBS based on the uniform theory of diffraction (UTD) and a human body model comprising lossy dielectric flat plates is proposed and verified. Then, the general forms of the formulas are predicted using the theory of knife-edge diffraction (KE). A series of computer simulations using the proposed calculation method with random changes in parameters is conducted to verify the general formulas and derive coefficients for these formulas through regression formulas.