移動(dòng)中繼協(xié)助下終端直通中面向能效的聯(lián)合中繼選擇和資源分配方案
doi: 10.11999/JEIT161359
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2.
(西安交通大學(xué)電子與信息工程學(xué)院 西安 710049) ②(西安交通大學(xué)軟件學(xué)院 西安 710049)
國(guó)家自然科學(xué)基金(61372092, 61531013),國(guó)家863計(jì)劃(2014AA01A707),江蘇省自然科學(xué)基金(BK20141214),教育部中國(guó)移動(dòng)科研基金(MCM20150102)
Energy-efficient Joint Relay Selection and Resource Allocation Scheme for Mobile Relay Aided Device-to-device Communication
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2.
(School of Electronics and Information Engineering, Xi&rsquo
The National Natural Science Foundation of China (61372092, 61531013), The National 863 Program of China (2014AA01A707), The Natural Science Foundation of Jiangsu Province (BK20141214), The Research Fund of Ministry of Education-China Mobile (MCM20150102)
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摘要: 在移動(dòng)中繼協(xié)助下的終端直通(Device-to-Device, D2D)中,由于頻帶復(fù)用,D2D鏈路與已有蜂窩鏈路會(huì)產(chǎn)生同頻干擾。另外,考慮到終端設(shè)備功率受限,該文提出一種聯(lián)合功率控制、信道分配和移動(dòng)中繼選擇方案最大化D2D鏈路總能量效率。原問(wèn)題為分?jǐn)?shù)規(guī)劃問(wèn)題,可轉(zhuǎn)化為通過(guò)Dinkelbach算法求解的參數(shù)規(guī)劃問(wèn)題,此外,上述參數(shù)規(guī)劃問(wèn)題可進(jìn)一步分解為功率控制子問(wèn)題和聯(lián)合優(yōu)化信道分配與移動(dòng)中繼選擇子問(wèn)題。其中,功率控制子問(wèn)題屬于DC(Difference-of-Concave)規(guī)劃問(wèn)題,其一般意義下為NP-hard難題,可借助序列凸優(yōu)化方法得到有效的近似解,基于上述結(jié)果,聯(lián)合優(yōu)化信道分配與移動(dòng)中繼選擇子問(wèn)題可轉(zhuǎn)化為二分圖中的最大匹配問(wèn)題,繼而借助匈牙利算法在多項(xiàng)式時(shí)間內(nèi)求得最優(yōu)解。通過(guò)仿真,驗(yàn)證了該方案在優(yōu)化能量效率的效果。
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關(guān)鍵詞:
- 終端直通 /
- 能量效率 /
- 分?jǐn)?shù)規(guī)劃 /
- DC(Difference-of-Concave)規(guī)劃 /
- 二分圖匹配
Abstract: In mobile relay-aided Device-to-Device (D2D) communication, the co-channel interference between D2D links and the existing links is inevitable due to spectral reuse. Besides, considering the limited battery lifetime of mobile terminals, a joint Power Control (PC), Channel Assignment (CA), and MR-selection scheme is proposed to maximize the global energy efficiency of MR-aided D2D communication. By exploring the property of fraction programming, the original problem can be transferred into solving a sequence of parametric programming problems via the Dinkelbach method. Besides, each parametric programming problem can be decomposed into two subproblems, i.e., the PC subproblem and the joint CA and MR selection subproblem. Moreover, the former turns out to be the Difference-of-Concave (DC), programming which is generally NP-hard, but it can be well addressed by sequential convex optimization technique. Based on the above results, the latter reduces to the bipartite matching problem which can be optimally solved by the Hungarian algorithm in polynomial time. Simulation results verify the efficacy of the proposed scheme. -
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