NASCOR: Network Assisted Spectrum Coordination Service for Coexistence between Heterogeneous Radio Systems

Raychaudhuri, Dipankar; Baid, Akash

doi:10.1587/transcom.e97.b.251

Cited by 6 publications

(7 citation statements)

References 25 publications

(24 reference statements)

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“…Coordination between multi‐RATs like WiFi and LTE is challenging due to the difference in the medium access layer of the two technologies. We have assumed that the architecture will be based on the principle of software‐defined radio . The goal of this architecture is to support information dissemination required for coordination of the HetNets.…”

Section: System Modelmentioning

confidence: 99%

Hierarchical decision model for throughput maximization in D2D‐enabled LTE‐WiFi HetNets

Gbenga-Ilori

Sezgin

2018

Trans Emerging Tel Tech

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This paper proposes a hierarchical decision model for efficient and fair coexistence of Wireless Fidelity (WiFi) and heterogeneous cellular networks with device‐to‐device (D2D) communications. The first submodel is an allocation game formulated to model the data rate gain possible through the deployment of D2D communication in cellular networks. This is to guarantee that the Long‐Term Evolution (LTE) network is optimally utilized before offloading traffic to WiFi small cells. The second submodel is a Markovian model proposed as an optimal spectrum sharing scheme that guarantees efficient spectrum utilization and interference reduction in LTE‐WiFi heterogeneous networks (HetNets). Simulation results verify that the proposed decision model not only provides a more spectrum efficient sharing scheme but also shows better network throughput while ensuring fairness in spectrum access for WiFi users.

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Section: System Modelmentioning

confidence: 99%

Hierarchical decision model for throughput maximization in D2D‐enabled LTE‐WiFi HetNets

Gbenga-Ilori

Sezgin

2018

Trans Emerging Tel Tech

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“…This is equivalent to the upper condition in (2) and 3, and (a) follows. (b) Let q W > 0 and q > 0. normalsize Then, by (12) and (13),…”

Section: Appendixmentioning

confidence: 99%

“…A goal of this paper is to design the most fair channel access protocol for a channel shared between LTE-U and Wi-Fi networks. The model studied in the paper is based on the model for coordinated dynamic spectrum management between LTE-U and Wi-Fi networks suggested in [13] and [14]. Namely, in [13], a system for coordinating between multiple heterogeneous networks to improve spectrum utilization and facilitate co-existence, which involves building a logically-centralized spectrum management controller using the principles of a Software Defined Networking was outlined.…”

Section: Introductionmentioning

confidence: 99%

“…The model studied in the paper is based on the model for coordinated dynamic spectrum management between LTE-U and Wi-Fi networks suggested in [13] and [14]. Namely, in [13], a system for coordinating between multiple heterogeneous networks to improve spectrum utilization and facilitate co-existence, which involves building a logically-centralized spectrum management controller using the principles of a Software Defined Networking was outlined. Based on this architecture, an optimization model to maximize the aggregated Wi-Fi+LTE throughput was designed and tested in [14].…”

Section: Introductionmentioning

confidence: 99%

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Bargaining over Fair Channel Sharing Between Wi-Fi and LTE-U Networks

Garnaev

Sagari

Trappe

2017

Lecture Notes in Computer Science

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Wireless networks are increasingly moving towards a heterogeneous operating model involving the sharing of spectrum resources by different access technologies. Sharing wireless resources between different wireless technologies requires protocols that share spectrum in an equitable manner. In this paper, we examine the time-sharing of wireless channels by Wi-Fi and LTE-U networks. To design fair access protocol for the networks we use α fairness criterion. It allows to find a continuum of fair protocols (a protocol per α). To find the most fair from this continuum of fair protocols we apply Nash bargaining approach. In particular, we show that such a time-sharing bargaining protocol, in spite of the interference between signals, can lead to a gain for both networks under an increase of the transmission power to one of them.

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“…Towards this end, the concept of a spectrum server has been introduced to improve the sharing of spectrum [1][2][3]. Spectrum servers coordinate the sharing of spectrum between different wireless services by taking in resource requests (i.e., an amount of bands needed), and then allocating resource assignments to these services.…”

Section: Introductionmentioning

confidence: 99%

Competitive Sharing of Spectrum: Reservation Obfuscation and Verification Strategies

Garnaev

Trappe

2017

Entropy

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Sharing of radio spectrum between different types of wireless systems (e.g., different service providers) is the foundation for making more efficient usage of spectrum. Cognitive radio technologies have spurred the design of spectrum servers that coordinate the sharing of spectrum between different wireless systems. These servers receive information regarding the needs of each system, and then provide instructions back to each system regarding the spectrum bands they may use. This sharing of information is complicated by the fact that these systems are often in competition with each other: each system desires to use as much of the spectrum as possible to support its users, and each system could learn and harm the bands of the other system. Three problems arise in such a spectrum-sharing problem: (1) how to maintain reliable performance for each system-shared resource (licensed spectrum); (2) whether to believe the resource requests announced by each agent; and (3) if they do not believe, how much effort should be devoted to inspecting spectrum so as to prevent possible malicious activity. Since this problem can arise for a variety of wireless systems, we present an abstract formulation in which the agents or spectrum server introduces obfuscation in the resource assignment to maintain reliability. We derive a closed form expression for the expected damage that can arise from possible malicious activity, and using this formula we find a tradeoff between the amount of extra decoys that must be used in order to support higher communication fidelity against potential interference, and the cost of maintaining this reliability. Then, we examine a scenario where a smart adversary may also use obfuscation itself, and formulate the scenario as a signaling game, which can be solved by applying a classical iterative forward-induction algorithm. For an important particular case, the game is solved in a closed form, which gives conditions for deciding whether an agent can be trusted, or whether its request should be inspected and how intensely it should be inspected.

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NASCOR: Network Assisted Spectrum Coordination Service for Coexistence between Heterogeneous Radio Systems

Cited by 6 publications

References 25 publications

Hierarchical decision model for throughput maximization in D2D‐enabled LTE‐WiFi HetNets

Hierarchical decision model for throughput maximization in D2D‐enabled LTE‐WiFi HetNets

Bargaining over Fair Channel Sharing Between Wi-Fi and LTE-U Networks

Competitive Sharing of Spectrum: Reservation Obfuscation and Verification Strategies

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