1-2hit |
Seiji FUKUSHIMA Takayuki SHIMAKI Kota YAMASHITA Taishi FUNASAKO Tomohiro HACHINO
Recent small cube satellites use higher frequency bands such as Ku-band for higher throughput communications. This requires high-frequency link in an earth radio station as well. As one of the solutions, we propose usage of bidirectional radio-on-fiber link employing a wavelength multiplexing scheme. It was numerically shown that the response linearity of the electro-absorption modulator integrated laser (EML) is sufficient and that the spurious emissions are lower enough or can be reduced by the radio-frequency filters. From the frequency response and the single-sideband phase noise measurements, the EML was proved to be used in a radio-on-fiber system of the cube satellite earth station.
Kota YAMASHITA Shotaro KAMIYA Koji YAMAMOTO Yusuke KODA Takayuki NISHIO Masahiro MORIKURA
In this study, a contextual multi-armed bandit (CMAB)-based decentralized channel exploration framework disentangling a channel utility function (i.e., reward) with respect to contending neighboring access points (APs) is proposed. The proposed framework enables APs to evaluate observed rewards compositionally for contending APs, allowing both robustness against reward fluctuation due to neighboring APs' varying channels and assessment of even unexplored channels. To realize this framework, we propose contention-driven feature extraction (CDFE), which extracts the adjacency relation among APs under contention and forms the basis for expressing reward functions in disentangled form, that is, a linear combination of parameters associated with neighboring APs under contention). This allows the CMAB to be leveraged with a joint linear upper confidence bound (JLinUCB) exploration and to delve into the effectiveness of the proposed framework. Moreover, we address the problem of non-convergence — the channel exploration cycle — by proposing a penalized JLinUCB (P-JLinUCB) based on the key idea of introducing a discount parameter to the reward for exploiting a different channel before and after the learning round. Numerical evaluations confirm that the proposed method allows APs to assess the channel quality robustly against reward fluctuations by CDFE and achieves better convergence properties by P-JLinUCB.