Common simulation parameters.
Cognitive radio has been introduced in order to solve the spectrum scarcity problem (Haykin 2005). Although having limited radio resources, we need lots of spectrum to deploy newly developed wireless applications. Meanwhile, a large portion of allocated spectrum is identified as unused by an actual radio spectrum measurement. Thus, a new access scheme which allows spectrum sharing between different wireless systems referred as dynamic spectrum access is required (Zhao & Sadler 2007). Dynamic spectrum access is based on cognitive radio technology which enables learning from and adapting to the external radio
As a way of spectrum sharing between licensed and unlicensed users, spectrum overlay approach is considered. In spectrum overlay networks, a primary network has a license for the exclusive use of the allocated spectrum. In contrast, a secondary network has lower access priority. While the primary users access the licensed spectrum wherever and whenever they want, the secondary users access the spectrum on condition that the transmission of the primary network is sufficiently protected, i.e., the interference to the primary network should be less than a predefined threshold.
There are two ways for satisfying the protection condition: Sensing-based and interference-constrained transmissions. In sensing-based transmission, as a means of avoiding interference, the secondary users sense the spectrum before they start transmission (Liang et al. 2007; Kim et al.). Only if the secondary users detect the white space, they can access the spectrum. Even during the transmission, if the primary user uses the spectrum, the secondary user has to stop transmission. In interference-constrained transmission, on the contrary, the secondary users are allowed to transmit during the primary user transmission (Gastpar 2007). However, the transmit power should be adjusted not to interfere the primary user transmission.
In this chapter, we compare the two transmission schemes in terms of achievable throughput of the secondary user and provide a criterion for the transmission mode selection of sensing-based transmission and interference-constrained transmission.
The rest of this chapter is organized as follows. Section 2 presents the system model for the sensing-based and interference-constrained transmissions. Throughput analyses for both of the schemes are followed in Section 3. The simulation results are shown in Section 4. In Section 5, the conclusion is drawn.
2. System Model
A coexistence scenario of spectrum overlay between primary and secondary networks is depicted in Fig. 1. Primary and secondary networks are deployed in the overlapping regions and use the same frequency band. In Fig. 1, there are pairs of transmitter and receiver for the primary and secondary networks. We define channel gains between each pair of transmitter and receiver as
The basic concept of spectrum overlay approach is to unlock licensed spectrum to secondary users. Secondary users can access the licensed spectrum on condition that their interference to primary users is limited. Possible solutions for this problem are sensing-based transmission and interference-constrained transmission. The difference of two schemes is based on the support for the simultaneous transmission.
In sensing-based transmission, the secondary user should sense the existence of the primary user in the licensed spectrum before transmission. Through the transmission, whenever the primary user accesses the licensed spectrum, the secondary user is required to stop transmitting and vacate the spectrum. Each secondary user frame is divided into a sensing slot and a data transmission slot. The time length that the secondary user senses the spectrum is sensing duration
3. Throughput Analysis
In this section, the achievable throughput of the secondary user by means of both sensing-based and interference-constrained transmission is presented and then compared in terms of location of terminals and the acceptable power level of the primary user.
3.1. Sensing-Based Transmission
The first thing to derive the secondary user throughput based on sensing-based transmission is evaluating the sensing accuracy. During the sensing duration,
In order to detect the existence of a random signal such as p(n), an energy detector is applicable (Kay 1998). The decision rule is written as
Two probabilities are defined in conjunction with the detection procedure: false alarm probability and detection probability. False alarm probability
False alarm probability
By rearranging (3) and (4) and canceling
3.2. Interference-Constrained Transmission
The secondary user throughput based on interference-constrained transmission is presented. Interference-constrained transmission allows the secondary user simultaneous transmission with the primary user. In this case, however, the primary user transmission also should be protected by means of power control of the secondary user. If the interference of the secondary user experienced by the primary receiver is strong, the power of the secondary transmitter should be lessened. Thus, the secondary user power is controlled so as to its interference at the primary receiver is lower than a predetermined threshold, i.e.,
In order to maximize the secondary user throughput, the optimal strategy is that the interference power of the secondary user meets the threshold, i.e.,
Notice that there is an interference term in (10) which is comes from the primary transmitter and degrades the secondary user throughput.
4. Simulation Results
In this section, the throughput performances of both the sensing-based and interference-constrained transmissions are evaluated by computer simulations. In a primary network, we assume that there is a primary transmitter and a primary receiver. Similarly, in a secondary network, there is a secondary transmitter and a secondary receiver.
We assume a cellular scenario where the primary network and the secondary network are over-deployed. Thus, we are interested in the distances between two terminals and base stations. The distance from the secondary transmitter to the primary receiver is denoted by
We consider the path loss and short-term fading as a channel model. Path loss exponent is assumed to be 4. In addition, Rayleigh block fading is assumed, where each of channel gain is circularly symmetric complex-Gaussian random variable. Hence, the channel gain
The primary user follows Markovian traffic, with arrival rate
Oppositely, under the interference-constrained transmission, the secondary user throughput as a function of the SNR of the primary user is shown in Fig. 3. Notice that the secondary user throughput decreases with the increase with the SNR of the primary user. Differently from the sensing-based transmission, as the SNR of the primary user increases, the interference from the primary transmitter greatly degrades the secondary user throughput as in (10). Similar to that of the sensing-based transmission, it is observed that the secondary user throughput increases with
Fig. 4 depicts the secondary user throughput of both the sensing-based and the interference-constrained transmission as a function of the interference threshold of the primary receiver. The secondary user throughput increases with the increase of
Fig. 5 shows the secondary user throughput as a function of the distance ratio
Fig. 6 shows the secondary user throughput as a function of the distance ratio
We have discussed the achievable throughput of both the sensing-based and interference-constrained transmission in cognitive radio networks. The derivations of both schemes are presented and their throughput performances have been compared in various environments via computer simulations. In conclusion, the sensing-based scheme is advantageous when the interference threshold is tight and the primary and secondary users are relatively close. Oppositely, the interference-constrained scheme is better when the interference threshold is loose and the primary transmitter and receiver are located far from the secondary user.
Gastpar M. 2007 On capacity under receive and spatial spectrum-sharing constraints.. 6 2 649 658, Feb. 2007
Haykin S. 2005 Cognitive radio: Brain-empowered wireless communications,. 23 2 201 220, Feb. 2005
Kay S. M. 1998Prentice-Hall, Upper Saddle River, NJ
Kim S. Lee J. Wang H. Hong D. Sensing Performance of Energy Detector with Correlated Multiple Antennas.. , Accepted for publication.
Liang Y. C- Zeng Y. Peh E. Hoang A. T. 2008 Sensing-throughput tradeoff for cognitive radio networks.. 7 4 1326 1337, Apr. 2008
Noh G. Lee J. Wang H. Kim S. Hong D. 2008 A new spectrum sensing scheme using cyclic prefix for cognitive radio systems., 1891 1895, May 2008
Zhao Q. Sadler B. M. 2007 A survey of dynamic spectrum access: Signal processing, networking, and regulatory policy. 24 3 79 89, May 2007