Spectrum trading in cognitive radio networks: A
market-equilibrium-based approach
Advisor ：Wei-Yeh Chen
Student ：楊
于
世

Reference

D. Niyato , E. Hossain, “Spectrum trading in cognitive radio
networks: A market-equilibrium-based approach,” IEEE
Wireless Commun., vol. 15, no. 6, pp. 71 - 80 , Dec. 2008 .
1
Outline









Introduction
Spectrum sharing and spectrum trading
Spectrum trading : Structure
Spectrum trading : Related issues
Spectrum trading : Solution approaches
System model
Equilibrium in spectrum sharing and pricing
Expectation and learning
Conclusion
2
Introduction(1/2)

Frequency spectrum is the scarcest(很稀少) radio resource in
wireless communication networks.

The concept of cognitive radio was introduced to improve the
frequency spectrum utilization in wireless networks
3
Introduction(2/2)

We introduce a market-equilibrium-based spectrum trading
mechanism that uses spectrum demand and supply of the
primary and secondary users, respectively(分別地).

Since spectrum supply is stochastic(隨機的) in nature, a
distributed and adaptive learning algorithm is used for the
secondary users to estimate(估計) spectrum price and adjust
the spectrum demand accordingly so that the market
equilibrium can be reached.
4
Spectrum sharing and spectrum trading(1/2)

Two major steps in spectrum sharing are spectrum
exploration(探測) and spectrum exploitation(利用).

The objectives of spectrum exploration are to discover and
maintain(保持) the statistics(統計) of spectrum usage, and
identify the spectrum opportunities.
5
Spectrum sharing and spectrum trading(2/2)

Spectrum trading is the process of exchanging spectrum,
which can be performed based on the exchange of different
resources or money.

Spectrum trading determines the structure of radio resource
selling and buying.

Pricing is a major issue in spectrum trading that determines the
value of the spectrum to the spectrum seller and buyer.
6
Spectrum trading : Structure

Single Seller (Monopoly) :The simplest structure of spectrum
trading arises when there is only a single seller in the system.

Multiple Sellers (Oligopoly) :This market structure consists of
multiple sellers offering radio spectrum to the market.

No Permanent Seller (Exchange Market) :In this market
structure there is no permanent(永久的) spectrum seller, and
all users have the right to access the spectrum.
7
Spectrum trading : Related issues

Spectrum Pricing

Spectrum Supply and Cost of Spectrum Sharing

Utility Function and Spectrum Demand

Competition and Cooperation in Spectrum Sharing
8
Spectrum pricing

Price plays an important role in spectrum trading since it
indicates the value of spectrum to both the seller and buyer.

For the buyer, the price paid to the spectrum seller would
depend on the satisfaction achieved through the usage of that
spectrum.

For the spectrum seller, the price determines its revenue(收入).
9
Spectrum supply and cost of spectrum
sharing

In a cognitive wireless system this spectrum supply can be in
terms of the number of frequency channels, the number of time
slots , or transmit power given the price charged to the buyer.

There are two types of cost : Fixed cost is incurred due to the
investment(投資) in infrastructure, variable cost is incurred
due to performance degradation(下降) resulting fro
sharing/selling the spectrum.
10
Utility function and spectrum demand

In spectrum trading, spectrum demand determines the amount
of spectrum the buyer wants to access for a given price so that
its satisfaction is maximized.

The spectrum demand function can be derived(取得) based on
maximization of utility of secondary users for a given price.
11
Competition and cooperation in spectrum
sharing(1/2)

A competition occurs when each of the cognitive radio entities
has its self-interest and is rational(合理的) about maximizing
its own benefit.

Competition can be among multiple spectrum sellers to
attract(引起) more buyers or among spectrum buyers to obtain
the best quality/quantity(量) of spectrum at the lowest possible
price.
12
Competition and cooperation in spectrum
sharing(2/2)

Entities involved(包含) in spectrum trading may have a choice
to cooperate so that a better solution can be achieved.

The sellers can cooperate to choose higher prices so that they
earn a profit higher than that in case of competition
13
Spectrum trading : Solution approaches

Microeconomic Approach

Classical Optimization Approach

Noncooperative Game

Bargaining(交易) Game

Auction(拍賣)
14
Microeconomic approach

The solution of this approach is based on market equilibrium,
which denotes(表示) a price for which spectrum demand
equals spectrum supply.

At a market equilibrium, the seller’s profit and buyer’s
satisfaction are maximized.
15
Classical optimization approach

A classical optimization formulation(規劃) consists of an
objective to be maximized/minimized and a set of
constraints(限制).

A classical optimization problem can be formulated by the
controller entities for spectrum trading to maximize the profit
of the spectrum owner by adjusting(調整) the specrum price.
16
Noncooperative game

In spectrum trading, multiple primary users offer prices to sell
spectrum to secondary users intending to maximize their
profits.

Noncooperative game formulations are widely used to analyze
and obtain an equilibrium solution that satisfies all of the
entities.
17
Bargaining game

A bargaining game formulation can be used in situations where
players can cooperate, and a player can influence(影響) the
action of other players in trading the radio spectrum.

In this game the players can negotiate(協商) and bargain(交易)
with each other.
18
Auction

Auction is performed by buyers who submit(屈服) their
bids(出價) to a seller.

The seller decides how much of and to whom to sell the
spectrum.

This auction is suitable for a situation where the price of the
resource is undetermined(未確定) and is variable with the
buyers’ requirements.
19
System model

The primary service controller broadcasts price information to
all secondary service controllers.

Then spectrum demands from the secondary service
controllers are fed back to the primary service controller to
update the price based on spectrum supply function.
20
21
Equilibrium in spectrum sharing and
pricing

The objective of the primary service is to maximize profit
through selling/sharing the radio spectrum with the secondary
service, the aim of the secondary service is to maximize the
satisfaction of the connections.
22
Expectation and learning(1/2)

We consider a learning algorithm, namely, GFM.

This algorithm uses recursive(遞迴) updating to obtain the
actual information under uncertainty(不確定的), which is the
price offered by the primary service.
pe [t + 1] = pe [t] + α[t](p[t]-pe[t])
23
Expectation and learning(2/2)

pe [t] is the estimated(估計) price by the secondary service at
time t, and p[t ]is the current price from the primary service.

In this learning algorithm the estimated price in the
previous(先前的) iteration(重複) is corrected in the direction
of error weighted by the learning rate, which is a function of
the observed(注意) price.
24
Spectrum demand and supply functions
25
convergence to the equilibrium price and size of allocated spectrum
26
Conclusion

這篇論文主要是根據頻譜之間的交易行為與一些模式做一
個概念性的介紹，看完之後也提供了我ㄧ些對頻譜分享的
一些新的想法，可以透過交易的方式來達到頻譜分享的效
果，往後也可以根據此篇論文為理論的基礎，幫助以後的
研究。
27