報(bào)告題目：Learning to maximize a convex quadratic function with application to intelligent reflection surface for wireless communication

報(bào) 告 人：羅智泉  加拿大皇家科學(xué)院院士，香港中文大學(xué)（深圳）副校長(zhǎng)、教授

主 持 人：葛  飛 湘潭大學(xué)副校長(zhǎng)、教授

報(bào)告時(shí)間：2021年9月18日下午15:00-16:00

報(bào)告地點(diǎn)：數(shù)學(xué)院南樓308

報(bào)告摘要：

In this talk we consider learning and optimizing a rank-2 convex quadratic function over K discrete variables. This problem arises from optimal design of a passive beamformer for intelligent reflecting surface (IRS) in order to maximize the overall channel strength. When the quadratic function (or channel state information) is known, we propose a linear time algorithm that is capable of reaching a near-optimal solution with an approximation ratio of (1+cos(π/K))/2, i.e., its performance is at least 75% of the global optimum for K ≥ 3. Furthermore we develop methods to learn and optimize the beamforming strategy when the quadratic function is unknown (i.e. in the absence of channel state information).

報(bào)告人簡(jiǎn)介：

羅智泉，加拿大皇家科學(xué)院院士，香港中文大學(xué)（深圳）副校長(zhǎng)、教授，深圳市大數(shù)據(jù)研究院院長(zhǎng)，IEEE/SIAM Fellow。長(zhǎng)期從事優(yōu)化理論、算法設(shè)計(jì)及無(wú)線(xiàn)通信研究，相關(guān)論文被IEEE等權(quán)威學(xué)術(shù)機(jī)構(gòu)7次評(píng)為年度最佳論文，榮獲美國(guó)Farkas獎(jiǎng)、Paul Y.Tseng連續(xù)優(yōu)化紀(jì)念獎(jiǎng)。2020年被聘為華為eLab實(shí)驗(yàn)室主任，主持研發(fā)的5G網(wǎng)絡(luò)優(yōu)化技術(shù)已落地華為GTS平臺(tái)。

　
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