This paper discusses novel joint (intracell and intercell) resource allocation algorithms for self-organized interference coordination in multicarrier multiple-input multiple-output (MIMO) small cell networks. The proposed algorithms enable interference coordination autonomously, over multiple degrees of freedom, such as base station transmit powers, transmit precoders, and user scheduling weights. A generic <inline-formula><tex-math notation="LaTeX"> $\alpha$</tex-math></inline-formula>-fair utility maximization framework is considered to analyze performance-fairness tradeoff and to quantify the gains achievable in interference-limited networks. The proposed scheme involves limited inter-base station signaling in the form of two step (power and precoder) pricing. Based on this decentralized coordination, autonomous power and precoder update decision rules are considered, leading to algorithms with different characteristics in terms of user data rates, signaling load, and convergence speed. Simulation results in a practical setting show that the proposed pricing-based self-organization can achieve up to <inline-formula> <tex-math notation="LaTeX">$100\%$</tex-math></inline-formula> improvement in cell-edge data rates when compared to baseline optimization strategies. Furthermore, the convergence of the proposed algorithms is also proved theoretically.
Self-Organizing Algorithms for Interference Coordination in Small Cell Networks
F. Ahmed,A. Dowhuszko,O. Tirkkonen
Published 2017 in IEEE Transactions on Vehicular Technology
ABSTRACT
PUBLICATION RECORD
- Publication year
2017
- Venue
IEEE Transactions on Vehicular Technology
- Publication date
2017-09-01
- Fields of study
Computer Science, Engineering
- Identifiers
- External record
- Source metadata
Semantic Scholar
CITATION MAP
EXTRACTION MAP
CLAIMS
- No claims are published for this paper.
CONCEPTS
- No concepts are published for this paper.
REFERENCES
Showing 1-39 of 39 references · Page 1 of 1
CITED BY
Showing 1-12 of 12 citing papers · Page 1 of 1