Two-Stage Stable Matching Based Dynamic Spectrum Allocation in Heterogeneous Networks

Abstract

This paper addresses the resource allocation problem for small cells in the two-tier heterogeneous networks (HetNets) with non-independent resource blocks (RBs) usability, which is prevalent in HetNets application. To formulate the correlations of different RBs to facilitate the resource allocation, a normalized pointwise mutual information (NPMI)-based coefficient is proposed, which is easy to compute and adapt based on the historical information about RBs usability. To obtain a fast allocation solution, a twostage stable matching-based dynamic spectrum allocation algorithm (TSSM) is proposed, which takes both network throughput and user performance as optimization metrics. Specifically, through robust preferable stable matching in the first stage and the iterative matchings with NPMI-based coefficient as the preference profiles in the second stage, the efficient matching solution can be obtained with low complexity and thus is well adapted to the requirement of the resource allocation in HetNets. The validity of the proposed coefficient in modeling the relevance of RBs usability and the benefit of its usage in the allocation algorithm is verified with typical spectrum usability related data. The extensive simulation results on various spectrum environment show the average probability of no RB to use following the proposed TSSM are reduced by more than 13.2%, and the robust requirement for users can be guaranteed better at the same time. Furthermore, the accumulated throughput of all users in the network increases by more than 19.4% on an average under different RBs usability environment. INDEX TERMS Heterogeneous networks, dynamic spectrum allocation, correlation of spectrum usability, two-stage stable matching.

Spectrum Knowledge and Real-Time Observing Enabled Smart Spectrum Management

“…Many proposed DSM frameworks, including SAS, LSA, and IEEE 1900.5 have taken spectrum database as the basic SOP information source [4], [16]. On the other hand, the collection and update of the SOP information in the spectrum database may be frequent to guarantee the validity of the information, cost of which is inconvenient especially in the dynamic spectrum environment [17], [18]. The third approach is the spectrum prediction, which determines the intending SOP usability through the analysis of the correlations in the spectrum occupancy statistics.…”

Spectrum Occupancy Prediction based on adaptive Recurrent Neural Networks

“…The role of spectrum awareness systems is observing the spectrum usage in the DSA system, and understanding the aspect of spectrum usage by the learning algorithm to achieve more efficient spectrum sharing in the DSA system. The spectrum awareness system can provide useful information in terms of spectrum usage, such as the time domain trend of duty cycle (DC), which can enhance the spectrum sensing performance [4] and an efficient medium access control (MAC) protocol design [5], [6].…”