Recently, we proposed a multi-user spatial multiplexing technique called the minimum mean square error filtering combined with singular value decomposition (MMSE-SVD) for a distributed multiple input multiple output (MIMO) network. Multi-user MMSE-SVD applies the MMSE filter at macro base station (MBS) to suppress inter-user interference (IUI) and inter-antenna interference (IAI), while the eigenmode filter constructed by SVD at user equipments (UEs) to suppress IAI. To improve the link capacity in multi-cell environment, the inter-cell interference (ICI) from adjacent macro-cells is taken into account in generating the MMSE filter. In this paper, we apply multi-user MMSE-SVD with ICI information to OFDM downlink and SC uplink to discuss the impact of number of multiplexed UEs.
We have previously proposed synchronized spread spectrum code division multiple access (SS-CDMA) as a method for short message communication using the Quasi-Zenith Satellite System (QZSS). In this paper, we have evaluated the time synchronization accuracy due to the sky view factor experimentally. The absolute time error to achieve a 100% cumulative probability density function (CDF) was evaluated to 26.5 ns when using an elevation mask of 30°. This means that it is possible to achieve 98% of the accommodation rate in the proposed synchronized SS-CDMA under the condition of a sky view factor of over 44%. The main cause of absolute time error is considered to be deterioration of the position dilution of precision (PDOP).
Nowadays, multiple-input multiple-output (MIMO) transmission becomes an essential technology for wireless communication systems. Because the MIMO transmission performance heavily depends on the propagation channel characteristics, those channel parameters have been investigated through various radio measurements. In this paper, we propose a parameter estimation refinement method based on the nonlinear conjugate gradient (NLCG) approach. In our proposal, the accurate propagation parameters are obtained with a few iterations without falling into the local maximum points of the likelihood function. The proposed method was evaluated through a computer simulation, and the results showed that the residual signal power ratio (RSPR) of the channel reconstructed was improved by approximately 17% compared with the space-alternating generalized expectation-maximization (SAGE) algorithm. The proposed method is expected to be utilized for channel measurements in the future work.
In powerline communication systems (PLC), suppression of impulsive noise is a challenging problem. One of the existing methods to mitigate impulsive noise is a deliberate blanking which removes the received samples that exceed a given threshold. However, if the received signal amplitude exceeds the blanking threshold, it may cause miss-detection of impulsive noise. Therefore, it is important to determine the blanking threshold properly. In this article, we theoretically analyze the impact of the blanking threshold selection on achievable performance, i.e., probability of impulsive noise detection (PoD), probability of false alarm (PoF), and bit error rate (BER) in multi-carrier PLC systems.
UWB radar in millimeter wave band (79 GHz) can provide very high range resolution since it can occupy a wider band than quasi-millimeter wave band (24/26 GHz). This letter proposes the use of a millimeter wave UWB radar for drone detection and experimentally investigates the reflection characteristics of a typical drone in the millimeter wave band compared with that in the quasi-millimeter wave band. First, the drone’s radar cross section (RCS) is clarified. Next, radar echo characteristics for a flying drone are discussed. As a result, we have confirmed that the RCS in the millimeter wave band is larger than that in the quasi-millimeter wave band and the echoes from the rotors, which are a unique feature of drone, can be observed.