MU-MIMO (Multi-User Multiple Input and Multiple Output) has been considered as a fundamental technology for simultaneous communications between a base station and multiple users. This is because it can generate a large virtual MIMO channel between a base station and multiple user terminals with effective utilization of wireless resources. As a method of implementing MU-MIMO downlink, Block Diagonalization (BD) was proposed in which the transmission weights are determined to cancel interference between multiple user terminals. On the other hand, Block Maximum Signal-to-Noise ratio (BMSN) was proposed which determines the transmission weights to enhance the gain for each user terminal in addition to the interference cancellation. As a feature, BMSN has a pseudo-noise for controlling the null depth to the interference. In this paper, to enhance further the BMSN performance, we propose the BMSN algorithm that has the pseudo-noise determined according to receiver SNR. As a result of computer simulation, it is confirmed that the proposed BMSN algorithm shows the significantly improved performance in evaluation of bit error rate (BER) and achievable bit rate (ABR).

In bistatic radar, it is important to suppress the undesired signals such as the direct propagated signal from transmitter and its multipath components. Conventionally, some suppression methods have been proposed. They are categorized into the method using a feedback system and the method which subtracts the replicas of the undesired signals. The former method may have the problem on the convergence of the suppression performance. The latter method requires the precise delay times of the undesired signals. In this paper we propose a new method to detect the target in digital terrestrial TV-based bistatic radar which is based on orthogonal frequency division multiplexing (OFDM), without any information on the undesired signals' delay times. In the proposed method, we adapt a scheme based on maximum signal to noise ratio (MSN) algorithm, which makes signal to interference plus noise ratio (SINR) maximum for the desired signal component. The maximum sensitivity is steered so as to match the path that exhibits the delay which relates to the target position, as if the search beam is steered along the direction in array signal processing. In the proposed method, "nulls" are also formed for other delay components to be suppressed simultaneously. In the frequency domain, the carrier components of the scattered signal divided by those of the reference signal indicate the delays caused by scattering. We call these divided carrier components "normalized received signal." The steered sensitivity and nulls are created by the weight which is applied to the normalized received signal in the frequency domain. We obtain the method to estimate the weight to achieve the maximum SINR in the delay estimation which also includes the compensation for the reduction of the weight's length caused by decorrelation among the delay components. The simulation results show that our proposed method without any information on the undesired signal's delays provides sufficient detection performance for the typical target compared to the conventional one.

For a LEO constellation system, it is important to optimize the orbit parameters to maximize the quality of communication service. At the Next-generation LEO System (NeLS) Research Center, the LEO parameters were evaluated for a mobile satellite communication system. A 2π constellation was selected to maintain a stable inter-satellite link (ISL). An elevation angle above 20 degrees was required for a service area of 70 degree of latitude. The performance of optical ISL terminals has since improved as a result of key technological developments at the NeLS Research Center. As a consequence, the constellation parameters for ISL have become more flexible. Furthermore, the ability of ground station to access two satellites has improved communication quality. In this paper, we address the optimum constellation parameters for dual-satellite coverage. An equation for determining the optimum inclination angle was derived from the constellation parameters. Moreover, by using the new constellation parameters, we found that the satellite network consists of a bi-directional Manhattan Street Network (MSN), and the ISL network structure was improved.