Quantified Discrete Spectrum Access (QDSA) Framework
Posted: 2 Apr 2015
Date Written: March 31, 2015
Dynamic spectrum sharing is essential for meeting the growing demand for RF spectrum. The key requirement for dynamic spectrum access system is ensuring coexistence of multiple heterogeneous RF systems sharing spectrum in time, space, and frequency dimensions. There are several technical, business, and regulatory challenges around defining and enforcing a dynamic policy that can provide simple, flexible, and efficient spectrum sharing and enable protection of spectrum rights. In this paper, we propose a framework for dynamic spectrum sharing paradigm that articulates spectrum rights in terms of quantified spectrum usage footprints at the lowest granularity of spectrum access. The proposed framework essentially enables treating RF-spectrum as a commodity that can be shared, traded in simple, flexible, and efficient manner.
Transmitters consume RF-spectrum by in terms of RF-power in space, time, and frequency dimensions. Receivers consume RF-spectrum in terms of constraining the RF-power in space, time, and frequency dimensions. The framework is based on discretized spectrum space model wherein spectrum usage by the transceivers is quantified at a sample point in the unit spectrum spaces. Thus, using proposed discrete spectrum consumption quantification (DSCQ) methodology, the spectrum assigned or utilized by a transmitter or receiver can be quantified. The discretization and quantification approach transforms spectrum into a commodity that can be exchanged with service providers, a policy that can be regulated, and a resource that can be precisely controlled for making an efficient use.
Within the QDSA framework, an entity that wishes to request spectrum access communicates with a Spectrum-access Policy Infrastructure (SPI). Here, the entity requesting spectrum access could be an individual transceiver, a wireless service provider, or a spectrum broker. The spectrum access request provides information about the transceiver positions, transceiver performance attributes, capabilities, and desired spectrum-access attributes (e.g. duration of spectrum access, SINR at the receiver).
The SPI communicates with Spectrum Analysis Infrastructure (SAI) in order to define spectrum-access footprints for the individual transceivers. SAI receives real time information regarding spectrum consumption from Spectrum Sensing Infrastructure (SSI). The SSI employs an external dense RF-sensor network and estimates usage of spectrum by individual transceivers in real time using advanced signal processing and learning algorithms.
SAI evaluates feasibility of coexistence and allocates quantified spectrum-access footprints to the individual transceivers of the spectrum-access request. SPI maps the spectrum-access footprints into an enforceable spectrum-access policy and spectrum-access is granted to the requesting entity.
By estimating utilized and available spectrum space in real time, SSI provides the ability to define and regulate a dynamic spectrum-access policy. When the spectrum usage footprint estimated by SSI violates the assigned spectrum usage footprint, SPI can void the spectrum-access policy and can take regulatory action.
Following are the key contributions of QDSA: The quantified approach of QDSA enables easier understanding and interpretation of the outcomes. With spectrum as quantified resource perspective, the spectrum trade conversation could be on the following lines: ”I have 'x' units of spectrum right now, I have given `y' units of spectrum to somebody and have 'z' units of spare spectrum which I would like to share or may be keep as a reserve”. QDSA enables spatial overlap of multiple RF-systems while protecting spectrum rights. This has a significant implication in devising spectrum sharing services with a large number of fine-grained spectrum-accesses in a geographical region. In our simulation results, we show that upto 100 small footprint RF-networks coexisting without harmful interference within 4.3 km x 3.7 km geographical region within a single frequency band . In addition to providing the ability to defining and regulating a quantified spectrum-access policy, discretization of spectrum space facilitates aggregating spectrum access opportunities in space, time, and frequency dimensions for efficient routing and allocation of spectrum. It enables provisioning redundancy to spectrum links in order to meet desired link quality under dynamic conditions. Spectrum aggregation facilitated by the proposed methodology helps building a bigger spectrum pool and thus enables building attractive business models for dynamic spectrum access.
Key References:  N. Khambekar, C. M. Spooner, V. Chaudhary, "On Improving Serviceability With Quantified Dynamic Spectrum Access", IEEE DySPAN 2014.
Keywords: Quantified Dynamic Spectrum Access, Spectrum Access System, Regulation of Dynamic Spectrum Access
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