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7. Super-resolution channel estimation for mmWave massive MIMO with hybrid precoding

Author

Hu, Chen, Dai, Linglong, Mir, Talha, Gao, Zhen, and Fang, Jun

Subjects
Computer Science - Information Theory
Abstract

Channel estimation is challenging for millimeter-wave (mmWave) massive MIMO with hybrid precoding, since the number of radio frequency (RF) chains is much smaller than that of antennas. Conventional compressive sensing based channel estimation schemes suffer from severe resolution loss due to the channel angle quantization. To improve the channel estimation accuracy, we propose an iterative reweight (IR)-based super-resolution channel estimation scheme in this paper. By optimizing an objective function through the gradient descent method, the proposed scheme can iteratively move the estimated angle of arrivals/departures (AoAs/AoDs) towards the optimal solutions, and finally realize the super-resolution channel estimation. In the optimization, a weight parameter is used to control the tradeoff between the sparsity and the data fitting error. In addition, a singular value decomposition (SVD)-based preconditioning is developed to reduce the computational complexity of the proposed scheme. Simulation results verify the better performance of the proposed scheme than conventional solutions., Comment: To appear in IEEE Transactions on Vehicular Technology. Simulation codes are provided to reproduce the results presented in this paper: http://oa.ee.tsinghua.edu.cn/dailinglong/publications/publications.html

Published
2017
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22. Incentive Models for Mobile Code Offloading to Improve it's Adaptability

Author

Mir, Talha Mahin and Prof. Satish Srirama

Abstract

Mobiilne pilvearvutus on viimastel aastatel populaarsemaks muutunud, kuna see toob mobiiliseadmetele mitmeid eeliseid. Mobiiliseadmed on enamasti piiratud ressurssidega, kuid pilvearvutustehnoloogiate abil suudavad need tõhusalt täita isegi väga ressursimahukaid ülesandeid. Pilves ressursimahukate ülesannete täitmiseks peavad mobiiliseadmed delegeerima need ülesanded pilvele, mille jaoks tänapäeval kasutatakse kahte peamist tehnikat: ülesannete delegeerimist ja koodi off-load'imist. Ülesannete delegeerimise mudelis kasutab mobiiliseade API kaudu pilve poolt pakutavaid veebiteenuseid. Koodi off-load'imise mudelis jagatakse rakendus osadeks, et tuvastada ressursimahukad ülesanded, mis seejärel edastatakse serverile kaugtöötlemiseks. Koodi off-load'imiseks on seni kasutatud erinevaid tehnikaid, kuid ükski neist pole majanduslikult elujõuline, mistõttu seda mudelit tööstuses sageli ei kasutata. Selles töös püüti lahendada probleeme, mille tõttu koodi off-load'imine on kallis ja pakuti välja koodi off-load'imise mudeli, mis muudab antud protsessi majanduslikult elujõuliseks. Oleme välja töötanud mänguteoreetilise mudeli, mis motiveerib mobiilikasutajaid oma seadmeid off-load'imiseks kasutama. Matemaatilise mudeli valideerimiseks on välja töötatud ka simulatsioon ja väike prototüüp., Mobile cloud computing has been rising in popularity in recent years due to the advantages it brings to the mobile devices. Mobile devices are mostly resource constrained and using cloud computing technologies they can perform even highly resource intensive tasks efficiently. For performing resource intensive tasks on the cloud, mobile devices need to delegate those tasks to the cloud for which two major techniques are in use today namely Task delegation and Code offloading. In task delegation model, mobile device consumes web services provided by the cloud through an API. Whereas in Code offloading model, app is partitioned to identify resource intensive tasks which are then transferred to the server for remote processing. Various techniques have been in use for performing code offloading but none of them are economically viable due to which this model is not frequently used in the industry. In this thesis, we tried to address the issues which make code offloading expensive and came up with code offloading model that can make the process economically viable. We developed a game theoretic model that provides incentive to mobile users to open their devices for offloading. Simulation and a small prototype have also been developed to validate the mathematical model.

Published
2018

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