PhD position in SYSCOM team of IETR laboratory (Rennes, France)
Start from October 2017, 3 years full-time job, academic funding
Required skill: MSc degree electronic, telecommunication, network, signal processing, applied mathematics. Strong mathematical (probability, integral calculus, special functions, matrix decomposition) and digital communication backgrounds (MAC-PHY layer, signal processing, information theory).
Host laboratory: IETR (Institute of electronic and telecommunication of Rennes, France, http://www.ietr.fr) regroups research staff from INSA of Rennes, CNRS, CentralSupelec Rennes, Nantes and Rennes universities
Host team: SYSCOM (systems and communication) involved in digital communication (signal, front-end architecture and MAC-PHY layer, cross-layer, heterogeneous network) and embedded systems research (system architecture, architecture management, design methodology)
School: INSA of Rennes, France (UBL, doctoral school MATISSE)
Start: October 2017, 36 months, full-time
Supervising: Jean-Yves Baudais (CR CNRS, HDR), Philippe Mary (MC INSA)
Funding: academic PhD contract
Scientific context: the stochastic geometry is a power-full framework to model and evaluate wide cellular wireless communication networks and to characterise the interference, the outage probability, the transmission capacity or the ergodic rate . Other metrics have been evaluated at IETR in the green radio context, combining stochastic geometry and random matrix theory results . The random geometry asset is to provide an analytic tool to evaluate the network performance. But, as the hexagonal and the Wyner models, the stochastic geometry model introduces bias in performance estimation depending on the point processes used (determinantal, Ginibre, Matern, Poisson...) and on the assumptions (overloaded network, peak transmit power, non cooperation, narrow band, Gaussian signaling...) . A trade-off occurs between the model relevance and the analytic tractability of the model. This stochastic geometry tool however allows the large scale evaluation and optimisation of new communication techniques. The obtained results in point to point can not be extended to large scale networks. The new communication techniques have to be optimised taking into account the network geometry. The pessimistic assumption of overloaded network is relaxed using a probability transmission or a conditional thinning of the point process . With overloaded cells, the time has to be considered with latency and transmission delay [4,5]. Similarly, the base station sleep mode for energy saving leads to reallocate the communication that could modify the transmission delay.
Objectives: study the trade-off capacity-delay to optimise cellular wireless networks. The PhD program will begin with a rigorous and strong state of the art. The theoretical analysis will be conducted and the results compared to simulation results. The PhD candidate will then propose transmission strategies, e.g. power allocation, scheduling, for the downlink and uplink scenario according to the application delay constraints.
 H. ElSawy, A.Sultan-Salem, M.S. Alouini, and M.Z. Win, "Modeling and analysis of cellular networks using stochastic geometry: A tutorial,'' IEEE Communications Surveys Tutorials, vol. PP, no. 99, pp. 1--37, 2016.
 A. Alam, P. Mary, J.-Y. Baudais, and X. Lagrange, "Energy efficiency-area spectral efficiency tradeoff in PPP network with SLNR precoder,'' in IEEE Workshop on Signal Processing Advances in Wireless Communications, (Edinburgh, UK), pp. 1--6, July 2016.
 H. Dhillon, R. Ganti, and J. Andrews, "Load-aware modeling and analysis of heterogeneous cellular networks'' IEEE Trans. Wireless Commun., vol. 12, pp. 1666--1677, April 2013.
 G. Zhang, T. Quek, A. Huang, and H. Shan, "Delay and reliability tradeoffs in heterogeneous cellular networks,'' IEEE Transactions on Wireless Communications, vol. 15, pp. 1101--1113, Feb. 2016.
 L. Chen, C. Liu, X. Hong, C.-X. Wang, J. Thompson, and J. Shi, "Capacity and delay tradeoff of secondary cellular networks with spectrum aggregation.'' arXiv:1612.08778, Dec. 2016.
Required skill: MSc degree electronic, telecommunication, network, signal processing, applied mathematics. Strong mathematical (probability, integral calculus, special functions, matrix decomposition) and digital communication backgrounds (MAC-PHY layer, signal processing, information theory)
How to apply: email
- Motivation letter
- Full CV with courses and projects that could be related to the topic
- Academic records (From BS to MSc)
- 2 or 3 references (with contact)
Contacts: email@example.com et firstname.lastname@example.org
(c) GdR 720 ISIS - CNRS - 2011-2015.