A novel optimization framework for resource allocation in wireless networks and radar systems is proposed, which merges the methods of maximum block improvement (MBI) and of sequential optimization. A detailed convergence proof is provided, showing that the proposed algorithm is able to monotonically increase the objective value while ensuring that every limit point of the generated variable sequence fulfills the problem first-order optimality conditions under very mild hypothesis. These results extend available convergence results on MBI and sequential optimization, significantly widening the range of applications that can be handled by the proposed framework compared to available approaches. This point is illustrated in detail presenting relevant applications from both the cellular and radar context, which fall under the umbrella of the developed optimization method.
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Manuscript received December 14, 2017; revised May 4, 2018 and July 28, 2018; accepted August 12, 2018. Date of publication September 3, 2018; date of current version November 13, 2018. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Wenwu Wang. The work of Drs. Augusto Aubry and Antonio De Maio was supported by the project Radar wAveform Diversity for spectrAlly cRowded envirOnments based on oPtimization (RADAROPT), funded by Dipartimento di Ingegneria Elettrica e delle Tecnologie dell’Informazione, Universitá di Napoli “Federico II”, 2017. The work of A. Zappone was supported by the European Commission through the H2020-MSCA IF-BESMART project under Grant Agreement 749336. (Corresponding author: Augusto Aubry.) A. Aubry and A. De Maio are with the Universitá degli Studi di Napoli “Federico II”, Dipartimento di Ingegneria Elettrica e delle Tecnolo-gie dell’Informatione, Napoli 80125, Italy (e-mail:, email@example.com; firstname.lastname@example.org).
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- Sequential optimization
- maximum block improvement (MBI) method
- radar systems
- wireless communication systems