Performance Improvement of Hybrid Cognitive Radio Networks with AF Relay

DOI : 10.17577/IJERTV4IS100324

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Performance Improvement of Hybrid Cognitive Radio Networks with AF Relay

Satheesan U

Electronics and Communication Engineering NSS College of Engineering

Palakkad, Kerala, India

Sudha T

Electronics and Communication Engineering NSS College of Engineering

Palakkad, Kerala, India

AbstractIn this paper, we consider the achievable data rate for the multiband cognitive radio networks with both Amplify-and-Forward (AF) and Decode-and-Forward (DF) relay in the cooperative transmission (CT) path. The DF relay performs the power auction mechanism to allocate optimum power to the secondary users (SUs). The SU participate in the auction mechanism and bids for maximum utility. After power allocation the AF relay performs the amplification process to achieve high data rate at the receiver.

Keywords-Cognitive Radio (CR), Power Auction,, DF Relay, AF Relay, Achievable Data Rate, Bit Error Rate.


    For wireless communication systems the radio spectrum is considered as the key resource. Throughout the world, the spectrum is divided into licensed and unlicensed bands. The licensed band is underutilized and the vacant frequency band in the spectrum is called the spectrum hole. CR is an upcoming and promising technology to utilize the spectrum in an ecient manner. Cognitive radio can be viewed as an intelligent wireless system built up of software defined radios which are able to constantly monitor the environment and adapt their communication in order to efficiently allocate the unused spectra. The power allocated to the SU should be controlled to reduce interference to primary users (PUs) [1]-[5].

    In a CR system, SUs senses the spectrum licensed by the PUs. The vacant spectrum holes in the spectrum are used by the SUs. In sensing based spectrum sharing, the SU first senses the status of PU and select an appropriate spectrum sharing mode based on the sensing result. If the PU is active, spectrum underlay mode is selected for communication. If the PU is idle, spectrum overlay mode is used for transmission. Hybrid cognitive radio network works in both overlay and underlay mode. In such network, after selecting the mode operation, the SR conducts a power auction mechanism to sell its power and SUs acts as players to bid for maximum utility. The power auction mechanism helps to reduce the interference to PUs. The DF relay performs the auction mechanism by using power bidding and allocation algorithm [6]. The power bidding and allocation algorithm is used to allocate optimum power to the SUs, according to its transmission mode. In the existing hybrid system model, DF relay performs the power bidding mechanism. DF relay does not amplify the signal in the

    cooperative path. As a result, the achievable data rate is limited in such networks. In this paper, AF relay is introduced in between the DF relay and secondary destination (SD), to provide improved signal to noise ratio (SNR) at the receiver. It is seen that achievable data rate and bit error rate of system are improved with the addition of an AR relay.

    The rest of this paper is organized as follows. In section II, system model is described. Section III gives the power auction mechanism used. Section IV describes the theory of AF relay. Simulation results are presented in Section V. Section VI concludes the findings of the paper.


    Consider a CR system consisting of a primary network, which is divided into M nonoverlapping narrowband channels and the secondary network is composed of N (N<M) secondary links. The primary network has a primary transmitter (PT) and a primary destination (PD). The secondary network consists of N secondary transmitters (STs), N secondary destinations (SDs), and a secondary relay (SR). The SR consists of a DF relay and an AF relay. The network model for both overlay and underlay mode is shown in Fig. 2. We had made the assumption that each channel of the primary network can be accessed by only one ST. The DF relay performs the power auction mechanism by organizing an auction game to sell its power. The SUs participate in the auction to buy its required power for data transmission. The AF relay in the system model amplifies the signal to give a high SNR at the receiver. So the achievable data rate is increased and BER is decreased.

    Fig. 1 Network model for Overlay and Underlay

    In spectrum overlay, the achievable data rate is given


    00 = 1 2(1 + 00(1) + 00(2)) (1)

    STi:initializes the required power (0) and original bid fi(0) and then submits these values to the relay.

    Step 3. Power Allocation


    where W is the signal bandwidth, 00(1) and 00 (2)

    SR:updates the allocated power (t + 1) and

    i i

    are the signal to noise ratio (SNR) in direct path and relay path of the ith user respectively.

    In spectrum underlay, the achievable data rate is given


    00 = 1 2(1 + 10(1) + 10(2)) (2)

    informthese values to each STs. Step 4. Bid Update

    STi:updates the bid value fi(t+1) and sends it back to the relay.

    Step 5. Convergence


    where 10 (1) and 10(2) are the SNR in direct path and Repeat Step 3 and Step 4 untill the value of fi(t) no

    i i

    relay path of the ith user respectively.


    If the ST works in spectrum overlay, it will transmit with high power budget ,for a high data rate. If the ST works in spectrum underlay, it adapts its power to to provide Quality of Service (QoS) guarantee to the PU [7].


    longer changes with additional iterations.


    In AF scheme, the relay rst amplies signals from the source and then cooperates with source to transmit secret information to the destination. In our model, the AF relay amplifies the signal from the DF relay and transmit it into the SD. As a result the SNR is improved at the receiver to

    | |

    = {




    ( ) , }

    provide high data rate and hence low BER [8]-[10].

    In amplify-and-forward transmission, the received signals


    of the source-destination, source-relay, and relay-

    The power value is updated according to the bid fi(t) during each iteration . The DF relay updates the power in proportion to its payment fi(t) (t ), i.e.,

    destination links, respectively, are

    0 = 0 + 0 (3)

    ( + 1) = min { , () ()


    1 = 1 + 1 (4)

    (() ())




    where t is the iteration index, is the total power of DF relay and

    2 1 2 (5)

    = 12 + 21 + 2 (6)


    1 ||2

    and it is straightforward to show that its SNR is


    = { ( 2) , .

    = (0

    | |




    + 1 + 22

    ) (7)

    The power bidding algorithm is given below. The SR decodes the data sent by the STs. If it decode successfully, that user can only participate in the current auction mechanism.

    Algorithm: Power bidding and allocation algorithm [6]

    Step 1. Request for cooperation

    STi:sends a request to the relay for cooperation. SR:responds the cooperation request of STi.

    STi:transmits data in rst phase.

    SR:if the received signal is not decoded successfully, it informs STi of the failure; else it allows STi to participate in the auction nd goes to step 2.

    Step 2. Initialization

    1 122

    = 2 (0 + 1 + 2 + 2)

    where is the amplication factor, 0, 1 and 2 are the scaling factors and z0, z1, z2 are the corresponding noise in the above links. 0, 1 and 2are the SNR in the three links and 2 is the noise variance.


    For simulation results we are considering 10 secondary users. Fig. 2 shows the achievable data rate of each user under three different scenarios. We are considering three cases for data transmission. In the first case, direct transmission (DT) between ST and SD is considered. In the second case data is transmitted with the help of a DF relay. This type of communication is called cooperative transmission (CT). In the third case an AF relay is introduced between the DF relay and SD. From the simulation results, it is clear that the achievable data rate is maximum with AF relay, then with DF relay and minimum for direct transmission (DT).

    Fig. 2 Achievable data of different users

    Fig. 3 shows the BER for 10 secondary users under the same three scenarios. The SNR used for simulation is 20dBm. From the results, it is clear that BER is minimum with AF relay due to the high SNR at the receiver. System with DF relay has a higher BER as compared to that of AF relay. Direct transmission has the highest BER as expected.

    Fig. 3 BER of different users


In this paper, we have investigated the effect of DF relay and AF relay on the achievable data rate and BER of the receivers in hybrid cognitive radio networks. By introducing an AF relay along with DF relay in the relay path, the performance of the hybrid cognitive radio network is improved. The DF relay performs the power bidding algorithm and AF relay improves the SNR of the signal at the receiver side. Hence the data rate and performance is improved.


This work is supported by AICTE, Govt. of India through the project grant under Research promotion Scheme No.20/AICTE/RIFD/RPS (POLICY- 1)59/2013- 14.


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