Abstract
In this work, we study the generalized degrees- of-freedom (GDoF) of downlink and uplink cellular networks, modeled as Gaussian interfering broadcast channels (IBC) and Gaussian interfering multiple access channels (IMAC), respectively. We focus on regimes of low inter-cell interference, where single-cell transmission with power control and treating inter-cell interference as noise (mc-TIN) is GDoF optimal. Recent works have identified two relevant regimes in this context: one in which the GDoF region achieved through mc-TIN for both the IBC and IMAC is a convex polyhedron without the need for time-sharing (mc-CTIN regime), and a smaller (sub)regime where mc-TIN is GDoF optimal for both the IBC and IMAC (mc-TIN regime). In this work, we extend the mc-TIN framework to cellular scenarios where channel state information at the transmitters (CSIT) is limited to finite precision. We show that in this case, the GDoF optimality of mc-TIN extends to the entire mc-CTIN regime, where GDoF benefits due to interference alignment (IA) are lost. Our result constitutes yet another successful application of robust outer bounds based on the aligned images (AI) approach.
Original language | English |
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Title of host publication | 2020 IEEE International Symposium on Information Theory (ISIT) |
Publisher | Institute of Electrical and Electronics Engineers |
Pages | 2936-2941 |
Number of pages | 6 |
ISBN (Electronic) | 978-1-7281-6432-8 |
DOIs | |
Publication status | Published - 24 Aug 2020 |
Externally published | Yes |
Event | 2020 IEEE International Symposium on Information Theory, ISIT 2020 - Los Angeles, United States Duration: 21 Jun 2020 → 26 Jun 2020 |
Conference
Conference | 2020 IEEE International Symposium on Information Theory, ISIT 2020 |
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Country/Territory | United States |
City | Los Angeles |
Period | 21/06/20 → 26/06/20 |
Funding
This work was partially supported by the European Research Council (ERC) under the ERC Advanced Grant N. 789190, CARENET.
Funders | Funder number |
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European Union's Horizon 2020 - Research and Innovation Framework Programme | 789190 |
H2020 European Research Council |