Robust Convergence of Energy and Computation for B5G Cellular Internet of Things

In beyond fifth-generation (B5G) cellular internet of things (IoT) networks, energy supply and data aggregation of a massive number of devices are two vitally challenging issues. To address these challenges, we propose a wireless powered MIMO over-the-air computation (AirComp) design framework. Firstly, wireless power transfer (WPT) is utilized to charge massive IoT devices simultaneously by exploiting the open nature of wireless broadcast channel. Then, AirComp is adopted to reduce latency of massive data aggregation via exploring the superposition property of wireless multiple-access channel. To realize efficient convergence of energy supply and data aggregation in practical IoT networks, a robust design algorithm is provided by jointly optimizing beamforming of both WPT and AirComp. Finally, extensive simulation results validate the robustness and effectiveness of the proposed algorithm over the baseline ones.

[1]  Jiaheng Wang,et al.  Worst-Case Robust MIMO Transmission With Imperfect Channel Knowledge , 2009, IEEE Transactions on Signal Processing.

[2]  Xiaoming Chen,et al.  Massive Access for Cellular Internet of Things Theory and Technique , 2019, SpringerBriefs in Electrical and Computer Engineering.

[3]  Arkadi Nemirovski,et al.  Lectures on modern convex optimization - analysis, algorithms, and engineering applications , 2001, MPS-SIAM series on optimization.

[4]  Kaibin Huang,et al.  MIMO Over-the-Air Computation for High-Mobility Multimodal Sensing , 2018, IEEE Internet of Things Journal.

[5]  G. Styan,et al.  Equalities and Inequalities for Ranks of Matrices , 1974 .

[6]  Hsiao-Hwa Chen,et al.  Enhancing wireless information and power transfer by exploiting multi-antenna techniques , 2015, IEEE Communications Magazine.

[7]  Slawomir Stanczak,et al.  Harnessing Interference for Analog Function Computation in Wireless Sensor Networks , 2013, IEEE Transactions on Signal Processing.

[8]  Dong In Kim,et al.  Distributed Random Access Scheme for Collision Avoidance in Cellular Device-to-Device Communication , 2015, IEEE Transactions on Wireless Communications.

[9]  Slawomir Stanczak,et al.  Nomographic Functions: Efficient Computation in Clustered Gaussian Sensor Networks , 2013, IEEE Transactions on Wireless Communications.

[10]  Omid Salehi-Abari,et al.  Over-the-air Function Computation in Sensor Networks , 2016, ArXiv.

[11]  Kaibin Huang,et al.  Reduced-Dimension Design of MIMO Over-the-Air Computing for Data Aggregation in Clustered IoT Networks , 2018, IEEE Transactions on Wireless Communications.

[12]  Xiaoming Chen,et al.  Wireless Powered Massive Access for Cellular Internet of Things With Imperfect SIC and Nonlinear EH , 2019, IEEE Internet of Things Journal.

[13]  M. Hata,et al.  Empirical formula for propagation loss in land mobile radio services , 1980, IEEE Transactions on Vehicular Technology.

[14]  Michael Gastpar,et al.  Computation Over Multiple-Access Channels , 2007, IEEE Transactions on Information Theory.