Orthogonal frequency-division multiplexing (OFDM) is one of the most widely used technologies in current wireless communication systems and standards. Cognitive radio (CR) provides a robust solution to the problem of spectrum congestion as it offers opportunistic usage of frequency bands that are not occupied by primary users. Due to the underlying sensing, spectrum shaping, scaling, and interoperable capabilities of OFDM, it has been adapted as a best transmission technology for CR wireless systems. However, the performance of an OFDM-based CR wireless system is affected by the existence of narrowband interference (NBI) from other users. Further, due to carrier frequency offset in NBI sources, NBI energy may spread over all subcarriers of an OFDM signal. In this paper, a fixed Amplify-and-Forward (AF) relay that operates at a frequency band that is different from that of direct mode is introduced to suppress the effect of NBI. Analytical expressions are derived for outage probability in direct, AF-relay, and incremental relaying modes. The outage performance of the proposed AF relay–based CR network is proven to be better than that of direct mode.
Cognitive radio (CR) uses the available radio spectrum opportunistically to cope with the growing number of bandwidth-limited wireless services [1]. In a CR network, secondary users effectively utilize the unused spectrums of the primary users. Orthogonal frequency-division multiplexing (OFDM) is employed in a CR system due to its inherent characteristics of spectrum sensing, spectrum shaping, scaling, and interoperable capabilities [2]. Further, OFDM reduces fading caused by multiple receptions of a signal and hence improves spectral efficiency.However, the performance of an OFDM-based CR system is affected by narrowband interference (NBI) from other wireless users. The following interference cancellation techniques are widely used in wireless communication systems: filter-based approach, cyclostationarity-based approach, higher-order statistics–based approach, transform domain approach, joint detection/multiuser detection (MUD), and spatial processing (for example, beamforming) [3]. Filter-based approaches were used to suppress NBI in OFDM-based conventional CR networks in [4]–[6]. In a coded OFDM system, NBI is suppressed by whitening the NBI spectrum using a prediction-error filter [4]. In [5], an interfering carrier frequency is estimated and cancelled using a notch filter. The success of this is dependent upon the accuracy of the estimation of the interfering carrier frequency. In [6], the active interfering tones in a multiband OFDM CR network are turned off and the resultant inter-carrier interference is suppressed using a notch filter. A higher-order statistics–based Bayesian decision theoretic approach is used to suppress partial-band interference in a frequency hop communication system [7]. However, this cannot be directly extended to an OFDM-based high-data-rate communication system due to its computational complexity. In [8], NBI is estimated by measuring the output signal energy, and receiver windowing is proposed to reduce the effect of NBI in an OFDM system.In [9], using a linear minimum mean square error–based estimator, unmodulated subcarriers are employed to measure NBI power. As the energy of NBI is different at each subcarrier, it is considered as a colored noise, which is then compensated for using an iterative decoder based on an expectation–maximization algorithm [10]. A constrained minimum mean-output-energy–based algorithm is developed for NBI estimation under the assumption that the second-order statistics of a received signal are known at the receiver [11]. The major issue with this method is its high computational complexity. Compressive sensing is used to estimate an NBI signal by exploiting its sparsity in the frequency domain [12]. The effects of NBI are analyzed in an ultra-wideband cooperative relay network in [13].Joint detection and MUD-based approaches were used for detecting secondary user symbols in the presence of a primary user signal, at the cost of high complexity [14]. In [15] and [16], interference is minimized in a CR system using the methods of opportunistic interference cancellation and phase adjustment, respectively. Amplify-and-Forward (AF) and Decode-and-Forward (DF) relaying protocols are used in cooperative communication networks to improve throughput and quality of service by exploiting spatial diversity [17]. The success of such a spatial processing technique has inspired us to use a cooperative AF half-duplex relay for interference cancellation. In this paper, the first major contribution is the introduction of a half-duplex AF relaying protocol in an OFDM-based CR network to suppress NBI. The use of such a relaying protocol provides spatial diversity and maximizes the output signal-to-interference-plus-noise ratio (SINR) of the CR network at each subcarrier of the OFDM signal. The second major contribution of this work is the derivation of the analytical expressions for analyzing the outage performance of the proposed OFDM-based cognitive AF relay network in the presence of NBI.The rest of the paper is organized as follows. A system model for an OFDM-based cognitive AF relay network is described in both the time domain and the frequency domain for direct and AF relay modes, in Section II. The analytical expressions are derived for the SINR of the direct and AF relay modes, in Section III. The outage performance of an OFDM-based CR network is analyzed for direct, AF-relay, and incremental relaying modes, in Section IV. Numerical results are presented in Section V, and concluding remarks are given in Section VI.Notations. Time-domain and frequency-domain vectors and matrices are denoted by aTD, aFD and ATD, AFD, respectively, and scalars are indicated by lowercase letters. An N × N discrete Fourier transform (DFT) matrix and an N × N identity matrix are denoted by FN and IN, respectively. An all-zero matrix of size m × n is denoted by 0m×n. The matrix complex conjugate transpose, complex conjugate, transpose, and inverse operations are denoted by ( )H, ( )*, ( )T, and ( )−1, respectively.
II. System Model
Consider the OFDM-based cognitive AF relay network with three secondary users shown in Fig. 1. Such a network can operate in two modes; namely, direct mode and AF relay mode. In direct mode, SU1 transmits data to SU3 in the first time slot. In AF relay mode, SU1 transmits data to SU2, which acts as a relay, during the first time slot. The signal at SU2 is amplified and forwarded to SU3 in the second time slot. The frequency bands FB1, FB2, and FB3, which are available for transmission/reception at each secondary user, are also indicated in Fig. 1. The received signals at SU2 in relay mode and SU3 in direct/relay modes are affected by NBI from other sources in the scenario. It is assumed that the first secondary user, SU1, has to transmit an OFDM signal to the third secondary user, SU3, through a frequency-selective fading channel. The OFDM signal has N subcarriers and uses v zero-padded guard subcarriers to suppress intersymbol interference [18].
In direct mode, SU1 transmits the OFDM signal to SU3 using the band FB1. The L1 × 1 channel impulse response (CIR) vector between SU1 and SU3 is defined as h13= [h13(0), h13(1), ... , h13(L1−1)]T. The L2 × 1 CIR vector of NBI source two at SU3 is defined as hb3 = [hb3(0), hb3(1), ... , hb3(L2−1)]T.The P × 1 time-domain received vector at SU3 is given bywhere P = N + v;
H 13 TD
and
H b3 TD
are P × P circulant matrices of an CIR vectors h13 and hb3, respectively; Fzp is a P × N zero-padded inverse DFT matrix at SU1 (it is defined as
F zp = [ F N 0 N×v ] Η ); x 1 FD
is a N × 1 data vector at N subcarriers of an OFDM symbol; and
b 3 TD
is a P × 1 NBI signal vector at SU3. The interference power per subcarrier (IPPS) of an NBI signal is denoted by
σ b3 2
;
z 3 TD
is a P × 1 zero-mean complex white Gaussian noise vector with elements that are independent and identically distributed with variance
σ z3 2
. The carrier frequency offset (CFO) for an NBI signal in band FB1 is represented by a P × P diagonal matrix
where β is a uniformly distributed random variable over the interval [−1/2, 1/2] [19]. By taking a DFT, the frequency-domain representation of the received vector
are diagonal matrices. Let λ13 = [λ13(0), λ13(1), ... , λ13(P−1)]T and λb3 = [λb3(0), λb3(1), ... , λb3(P−1)]T be P-point DFTs of h13 and hb3, respectively. Then, the matrices
H 13 FD
and
H b3 FD
are defined as
H 13 FD
= diag {λ13(0), λ13(1), ... , λ13(P−1)} and
H b3 FD
= diag {λb3(0), λb3(1), ... , λb3(P−1)}. Now, (2) can be simply written aswhere V = FPFzp is the precoding matrix;
A 3 (1),FD =F P A3 (1),TD F P H
is a circulant matrix of CFO at SU3; and
b 3 FD
and
z 3 FD
are the NBI signal and noise vectors in the frequency domain, respectively. The P × 1 NBI signal vector the vector
b 3 FD
is sparse in nature and indicates that
b 3 FD
contains only a few non-zero elements. The kth subcarrier element b3(k) ≠ 0 if k ∈ Ib3, where Ib3 is a set that contains an index of the non-zero elements which is NBI affected subcarriers.
- 2. AF Relay Mode
In AF relay mode, SU1 transmits an OFDM signal to SU2 using the band FB2 in the first time slot. The L3 × 1 CIR vector between SU1 and SU2 is defined as h12 = [h12(0), h12(1), ... , h12(L3−1)]T. The L4 × 1 CIR vector between NBI source one and SU2 is defined as hb2 = [hb2(0), hb2(1), ... , hb2(L4−1)]T. The P × 1 time-domain received vector
y 12 TD
at SU2 is given bywhere
H 12 TD
and
H b2 TD
are the P × P circulant matrices of the CIR vectors h12 and hb2, respectively. In addition,
b 2 TD
and
z 2 TD
are the NBI signal and noise vectors at SU2, respectively, and
A fo,2 (2),TD
is the CFO of the NBI signal in band FB2. By taking a DFT, the frequency-domain representation of the received vector
y 12 TD
is given bySince
H 12 TD
and
H b2 TD
are circulant matrices, (5) can be simplified aswhere
H 12 FD
and
H b2 FD
are the diagonal matrices of the vectors λ12 and λb2, respectively, and
A 2 (2),FD =F P A2 (2),TD F P H
is a circulant matrix.In the second time slot, the node of SU2 plays as an AF relay. It amplifies the received signal
y 12 TD
and forwards it to SU3 using the band FB3. The L5 × 1 CIR vector between SU2 and SU3 is defined as h23 = [h23(0), h23(1), ... , h23(L5−1)]T The L6 × 1 CIR vector of NBI source two at SU3 is defined as hb3 = [hb3(0), hb3(1), ... , hb3(L6−1)]. The time-domain received vector
y 23 TD
at SU3 is given bywhere
ρ= Ρ s / ( Ρ s σ h 2 + σ b2 2 + σ z2 2 )
is the amplification factor at SU2;
σ h 2 =E[ | h 12 | 2 ]
is the instantaneous squared-norm of the CIR vector
h 12 ; P s =E[ | x 1 FD | 2 ]
is the transmitted source power, which is the same as in SU2;
σ b2 2
is the IPPS of the NBI signal vector
b2 TD
;
σ z2 2
is the variance of the noise vector
z 2 TD
; and
H 23 TD
and
H b3TD
are the circulant matrices of the CIR vectors h23 and hb3, respectively. In addition,
A fo,3 (3),TD
,
b 3TD
, and
n 3TD
represent the CFO for NBI in band FB3 and the NBI signal and noise vectors at SU3, respectively. Substituting (4) in (7), the received vector
y 23TD
is written asBy taking a DFT, the frequency-domain representation of the received vector
y 23TD
is given bywhere
H 23 TD
,
H 12 TD
,
H b2 TD
, and
H b3TD
are circulant matrices. By decomposing them, (9) can be simplified asLet λ23 = [λ23(0), λ23(1), ... , λ23(P−1)]T and λb3 = [λb3(0), λb3(1), ... , λb3(P−1)]T be P-point DFTs of h23 and hb3, respectively. The elements of the diagonal matrices
H 23FD
and
H b3FD
are the vectors λ23 and λb3, respectively;
A 3 (3),FD =F P A3 (3),TD F P H
is a circulant matrix.
III. SINR Analysis
In this section, the analytical expressions for the SINR of the received signals at relay and destination nodes are derived at each subcarrier in both direct and AF relay modes.
- 1. Direct Mode
From (3), the direct-mode receive signal
y 13FD
at the kth subcarrier is given byIn this expression, the first term is the desired signal, where x1(k) is the kth subcarrier source data. The second and third terms denote the residual zero-padded interference and NBI signal, respectively. Since
A 3 (1),FD
is a circulant matrix, the third term is written as a circular convolution. The fourth term represents the noise at the kth subcarrier.Assuming that the CIR vectors λ23 and λb3 are perfectly known, the instantaneous SINR of the direct-mode receive signal
y 13FD
at the kth subcarrier is given byUsing the Cauchy–Schwartz inequality, the first term in the denominator of (12) can be expressed asSince
∑ q=0 N−1 | v(k,q) | 2 =1,
the term
∑ q=0,q≠k N−1 | v(k,q) | 2
can be simplified as 1 − |v(k, k)|2 ; then (13) can be written asSimilarly, the second term in the denominator of (12) can be expressed aswhere
ς 3 = ∑ m=0,m∈ I b3 P−1 | a 3 1 ( k, (m−k) P ) | 2
is the squared-norm of the CFO term and
σ b3 2 =E( ∑ m=0,m∈ I b3 P−1 | b 3 (m) | 2 )
is the IPPS of the NBI term. Now, substituting (14) and (15) in (12), the lower bound of Γ13(k) is simply written aswhere
σ z3 2
= E(|z3(k)|2) is the noise variance. Dividing the numerator and denominator by the source power Ps, we getwhere SIR 1 = Ps /
σ b3 2
and SNR = Ps /
σ z3 2
.
- 2. AF Relay Mode
In AF relay mode, a transmit signal passes through the two different channels h12 and h23 with amplification factor ρ at SU2. The SINR between SU1 and SU3 at the kth subcarrier in AF relay mode, Γ123(k), is given by [21] aswhere ΓIJ(k) is the SINR of the link joining SUI and SUJ, I, J ∈ (1, 2) . The SINR of the link joining SU1 and SU2 is determined as follows. From (6), the received signal
y 12FD
from SU1 to SU2 at the kth subcarrier is given byIn this expression, the first term is the desired signal. The second and third terms denote the residual zero-padded interference and the NBI signal, respectively. The fourth term is the noise. The instantaneous SINR of the received signal y12(k) is given byThe first and second terms in the denominator of (20) can be simplified asandrespectively, where
ς 2 = ∑ m=0,m∈ I b2 P−1 | a 2 2 ( k, (m−k) P ) | 2
is the squared-norm of the CFO term and
σ b2 2 =( ∑ m=0,m∈ I b2 P−1 | b 2 (m) | 2 )
is the IPPS of the NBI term. Substituting (21) and (22) in (20), we getwhere SIR2 = Ps /
σ b2 2
and SNR = Ps /
σ z2 2
, and
σ z2 2
is the noise variance. The instantaneous SINR of the received signal
y 23FD
can be expressed asThe first and second terms in the denominator of (24) can be simplified asandrespectively, where
ς 3 ″ = ∑ m=0,m∈ I b3 P−1 | a 3 3 ( k, (m−k) P ) | 2
is the squared-norm of the CFO and
σ b3 2 =( ∑ m=0,m∈ I b3 P−1 | b 3 (m) | 2 )
is the IPPS of the NBI term. Substituting (25) and (26) in (24), we getwhere
SIR3= P s / σ b3 2 , SNR=P s / σ n3 2
and
σ n3 2 =E( | n 3 ( k ) | 2 )
is the noise variance. In AF relay mode, the maximum data transfer rate depends on the minimum value between Γ12(k) and Γ23(k). Hence, the SINR Γ123(k) in AF mode is written as
IV. Performance Analysis
In this section, the outage performance of the OFDM-based cognitive AF relay network is analyzed at the subcarrier level in direct and AF relay modes for the data rate of R b/s/Hz. In addition, outage of the incremental AF relay is analyzed.
- 1. Outage Probability Analysis in Direct Mode
In direct mode, the upper bound of the outage probability of Γ13 at the kth subcarrier for the given data rate of R b/s/Hz is defined asLet the threshold SINR γ1 = 2R − 1. Then, the upper bound of
P out,k dir (R)
can be written asThe probability density function (PDF) of Γ13(k) is determined as follows. Let (17) be defined aswhere
, and d = 1/SNR. The random variables X and Y are exponentially distributed, and Z is chi-square distributed with 2r degrees of freedom [22]; the cardinality of the NBI signal vector is r. The PDF of the variables X, Y, and Z are given, respectively, bySince the desired signal channel and the interference channel are negatively quadrant dependent [23], the outage probability of X for the given random variables Y and Z is given bySince |v(k, k)| ≈ 1 and a ≈1, (35) can be simplified asEvaluating the inner integral by substituting (32), it becomesNow, (37) can be rewritten asSubstituting (33) and (34) in (38), then integrating, the outage probability is determined asSubstituting b, c, d, and γ1, the outage probability of the direct-mode SINR in terms of the data rate is given by
- 2. Outage Probability Analysis in AF Relay Mode
The outage probability for AF relay–mode SINR, ΓAF, at the kth subcarrier is defined asSince maximal ratio combining is applied at the destination in the second time slot, the AF relay–mode SINR ΓAF is defined as ΓAF(k) = Γ13(k) + Γ123(k) . Now, (41) can be written asGiven the threshold SINR γ1 for Γ13(k) , the lower bound of the AF outage probability is given byLet γ2 = 22R−1−γ1. Then, (43) can be written aswhere fΓ123(γ2) and fΓ13(γ1) are PDF functions of Γ123(k) and Γ13(k), respectively.Since Γ123(k) is the minimum of Γ12(k) and Γ23(k), the cumulative distribution function (CDF) of Γ123(k) can be written as [21]Using (39), the CDF of Γ12(k) is computed asBy using the approximations (1 + (a/r))−r ≈ exp(−a) and |v(k, k)|2 ≈ 1, (46) can be simplified asSimilarly, the CDF of Γ23(k) can be expressed asSubstituting (47) and (48) in (45), the CDF of of Γ123(k) is obtained asLet
g 2 =( 2 SNR + ς 2 SIR2 + ς 3 ″ SIR3 ).
Then, it can be written asDifferentiating (50) with respect to γ2, the PDF of Γ123(k) is determined asUsing (39), the CDF of Γ13(k) is given byIt can be simplified aswhere g1 = (1/SNR + ς3/SIR1). Then, the PDF of Γ13(k) is determined asSubstituting the PDF of Γ13(k) in (44) and evaluating the inner integral, we getSubstituting the PDF of Γ13(k) in (55), the lower bound of the outage probability for AF relay mode is determined as
- 3. Outage Probability for Incremental AF Relaying
In AF relay mode, a relay transmits the amplified received signal at the data rate of R b/s/Hz through a specified channel for the duration of the signal transmission. Indirectly, it reduces the number of degrees of freedom of the channel. But, in incremental AF relaying protocols, data is transmitted at either R/2 b/s/Hz or R b/s/Hz. The AF relay transmits data at the rate of R/2 b/s/Hz only if the direct-mode transmission fails to send the data at the data rate of R b/s/Hz, thereby an incremental AF relay network utilizes the relay channel effectively and improves the system performance [17]. The outage probability of the incremental AF relay mode is given byIn an incremental AF relaying protocol, the intersection of the direct mode and AF relay mode outage probabilities is exactly the AF relay mode outage probability at half the rate of the data rate. Therefore, it can be written asUsing (56), the lower bound of the outage probability of the incremental AF relay mode is given by
V. Numerical Results
The outage performance of the proposed OFDM-based CR relay network is analyzed in the presence of an NBI signal for direct, AF relay, and incremental AF relay modes. The simulation parameters are listed in Table 1.
Simulation parameters of cognitive AF relay network.
S. No
Parameters
Value
1
Number of subcarriers in OFDM signal, N
64
2
Guard sequence length, v
16
3
Number of channel taps, L
10
4
Number of subcarriers with NBI, r
1, 3, 5
5
CFO parameter of NBI signal, β
0.5
6
Data rates (in b/s/Hz), R
0.5, 1, 2, 3
7
Signal to NBI interference ratio (in dB)
10, 15, 20, 25
The outage performance of the proposed cognitive AF relay network in direct mode is shown in Fig. 2 for the data rate of 1 b/s/Hz. The SIR is varied from 10 dB to 25 dB. It is observed that the analytical results are very close to the simulation results. As the noise dominates NBI at low SNR, the effect of NBI is more significant at high SNR. In direct mode, as the SIR increases from 20 dB to 25 dB, the outage probability decreases from 1 × 10−2 to 3 × 10−3 at the data rate of 1 b/s/Hz and SNR per subcarrier of 30 dB.
Outage performance of proposed cognitive AF relay network in direct mode at 1 b/s/Hz.
Figure 3 shows the outage performance of the OFDM-based cognitive AF relay network in direct mode for the data rates 1 b/s/Hz and 2 b/s/Hz. It is observed that when the data rate is increased from 1 b/s/Hz to 2 b/s/Hz, the minimum SNR requirement increases from 20 dB to 25 dB in the absence of NBI to operate the network at the maximum outage probability of 1 × 10−2. The minimum SNR requirement rises to 30 dB SNR with a data rate of 1 b/s/Hz at an SIR of 20 dB.
Outage performance of proposed cognitive AF relay network in direct mode at 1 b/s/Hz and 2 b/s/Hz.
The outage performance for the proposed OFDM-based CR network in AF relay mode transmission is shown in Fig. 4 at the data rate of 1 b/s/Hz for different SIR values. Since the maximal ratio combining provides diversity gain at the destination node, the minimum SNR requirement decreases to 15 dB from 20 dB in the direct mode transmission at the outage probability of 1 × 10−2. In AF relay mode at 30 dB SNR, as the SIR increases from 20 dB to 25 dB, the outage probability decreases from 1 × 10−3 to 1 × 10−4 at the data rate of 1 b/s/Hz.
Outage performance of AF mode transmission at 1 b/s/Hz.
The outage performance of the proposed cognitive network in AF relay mode for the data rates of 1 b/s/Hz and 2 b/s/Hz is shown in Fig. 5. It is observed that when the data rate moves from 1 b/s/Hz to 2 b/s/Hz, the minimum SNR requirement to operate the network at the maximum outage probability of 1 × 10−2 increases from 15 dB to 22 dB in the absence of NBI, and for the SIR level of 20 dB, it further rises to 17 dB SNR with a data rate of 1 b/s/Hz and exceeds the limit at a data rate of 2 b/s/Hz.
Outage performance in AF relay mode at 1 b/s/Hz and 2 b/s/Hz.
The outage performance at the direct and AF relay modes is compared in Fig. 6. It is observed that the AF mode provides 5 dB SNR gain compared to the direct mode in the absence of NBI. At 30 dB SNR, when the mode is switched from direct to AF relay, the outage probability decreases from 1 × 10−2 to 1 × 10−3 at a data rate of 1 bit/s/Hz with 20 dB SIR.
Comparison of outage performance in AF relay mode and direct mode at 1 b/s/Hz.
In Fig. 7, the outage performance of the proposed OFDM-based CR network in AF relay mode is compared with direct mode for various relay interference values. The data rate is 1 b/s/Hz. In this Figure, RY and DS denote the relay and destination nodes, respectively. It is noted that the outage probability decreases from 1 × 10−3 to 4 × 10−4 when relay node operates with no NBI, at 30 dB SNR per subcarrier. In direct mode, the outage probability of the network is 1 × 10−2 for an SIR of 20 dB and an SNR of 30 dB. It indicates that the proposed network with limited interference at the relay performs better than the direct mode.
Comparison of outage performance in AF relay and direct modes at 1 b/s/Hz, with and without NBI at relay.
In Fig. 8, r represents the number of subcarriers that are directly affected by NBI. The outage performance of the proposed CR network in direct mode is shown in Fig. 8 at a data rate of 1 b/s/Hz for different r values. At 30 dB SNR, when r decreases from five to three, the outage probability decreases from 4.4 × 10−2 to 2.7 × 10−2; furthermore, it reduces to 1 × 10−2 when r = 1.
Outage performance of proposed cognitive AF relay network in direct mode at 1 b/s/Hz for various r values.
The outage performance of the AF relay and incremental AF relay modes is compared in Fig. 9. It is observed that for the outage probability of 1 × 10−4, the incremental AF relay mode provides 5 dB SNR gain compared to the AF relay mode, in the absence of NBI. This is due to the additional degree of freedom in the incremental AF relay mode.
Comparison of outage performance in AF relay and incremental AF relay modes at 1 b/s/Hz.
The outage performance of the AF relay mode for the data rates between 0.5 b/s/Hz and 3 b/s/Hz is shown in Fig. 10. At a low data rate, the outage is exactly reduced by 1 × 10−1 for every 5 dB increase in SIR level. For the maximum outage probability of 1 × 10−2, the CR network supports a data rate of up to 2 b/s/Hz at 25 dB SIR.
Outage performance of AF relay mode vs. transmission rates for fixed SNR = 40 dB.
VI. Conclusion
In this paper, a fixed AF relaying protocol is introduced in an OFDM-based CR network to suppress the effect of NBI. The performance of the CR network with an AF relay is analyzed in terms of outage probability. It is shown that the use of the AF relay suppresses the effect of NBI and that the outage performance is improved by 5 dB per subcarrier compared to the direct-mode transmission at a data rate of 1 b/s/Hz. Further, the outage performance is improved by the incremental AF relaying, where the system is operated at variable rate nature. It is found that for no NBI at the relay node, the outage of the system is significantly reduced. Finally, we conclude that the effect of the NBI can be reduced by the AF relay protocol in an OFDM-based cognitive radio system at constant data rate.
BIO
Corresponding Authorssraj.tce@gmail.comSamikkannu Rajkumar received his BE degree in electronics and communication engineering from the Angala Amman College of Engineering and Technology, Tamil Nadu, India, in 2000 and his ME degree in communication systems from Thiagarajar College of Engineering, Tamil Nadu, India, in 2006. At present, he is working as a full-time research scholar with the Department of Electronics and Communication Engineering, Thiagarajar College of Engineering, Tamil Nadu, India. His current areas of research include developing algorithms in cooperative relay networks and multiple antenna systems.
vnsenthilkumaran@tce.eduV.N. Senthilkumaran received his BE degree in electronics and communication engineering from VelTech Engineering College, Tamil Nadu, India, in 2002. He obtained his ME degree in communication systems from S.R.M. Engineering College, Tamil Nadu, India, in 2004 and his PhD degree in the area of wireless relay network design from Anna University, Tamil Nadu, India, in 2014. At present, he is working as an assistant professor with the Department of Electronics and Communication Engineering, Thiagarajar College of Engineering, Tamil Nadu, India. His current areas of research include physical-layer network coding and capacity analysis of wireless networks.
sjtece@tce.eduS.J. Thiruvengadam received his BE degree in electronics and communication engineering from Thiagarajar College of Engineering, Tamil Nadu, India, in 1991. He obtained his ME degree in applied electronics from the College of Engineering, Tamil Nadu, India, in 1994 and his PhD degree in the area of signal detection algorithms from Madurai Kamaraj University, Tamil Nadu, India, in 2005. At present, he is working as a professor with the Department of Electronics and Communication Engineering, Thiagarajar College of Engineering. Previously, he was a visiting associate professor with the Department of Electrical Engineering, Stanford University, CA, USA, under a postdoctoral fellowship sponsored by the Department of Science and Technology, Government of India, from January to December 2008. His current areas of research include statistical signal processing and multiple-input and multiple-output wireless communications.
Baum C.W.
,
Pursley M.B.
1992
“Bayesian Methods for Erasure Insertion in Frequency-Hop Communication Systems with Partial Band Interference,”
IEEE Trans. Commun.
40
(7)
1231 -
1238
DOI : 10.1109/26.153368
Redfern A.J.
2002
“Receiver Window Design for Multicarrier Communication Systems,”
IEEE J. Sel. Areas Commun.
20
(5)
1029 -
1036
DOI : 10.1109/JSAC.2002.1007383
Sanguinetti L.
,
Morelli M.
,
Poor H.V.
“Robust EM-Based Detection of BICM-OFDM Transmissions in the Presence of Narrowband Interference,”
IEEE European Wireless Conf.
Lucca, Italy
Apr. 12–15, 2010
696 -
700
Maichalernnukul K.
,
Kaiser T.
,
Zheng F.
“Performance of Ultra-wideband Cooperative Relay Systems in the presence of Narrowband Interference,”
IEEE Int. Conf. Ultra-wideband
Bologna, Italy
Sept. 14–16, 2011
405 -
409
Hassan M.H.
,
Hossain Md. J.
2013
“Cooperative Beamforming for Cognitive Radio Systems with Asynchronous Interference to Primary User,”
IEEE Trans. Wireless Commun.
12
(11)
5468 -
5479
DOI : 10.1109/TWC.2013.092013.121275
Muquet B.
2002
“Cyclic Prefixing or Zero Padding for Wireless Multicarrier Transmissions?”
IEEE Trans. Commun.
50
(12)
2136 -
2148
DOI : 10.1109/TCOMM.2002.806518
Rabiei P.
,
Namgoong W.
,
Al-Dhahir N.
2011
“On the Performance of OFDM-Based Amplify-and-Forward Relay Networks in the Presence of Phase Noise,”
IEEE Trans. Commun.
59
(5)
1458 -
1466
DOI : 10.1109/TCOMM.2011.030411.100206
@article{ HJTODO_2015_v37n3_460}
,title={Outage Analysis of OFDM-Based Cognitive AF Relay Network in the Presence of Narrowband Interference}
,volume={3}
, url={http://dx.doi.org/10.4218/etrij.15.0114.0300}, DOI={10.4218/etrij.15.0114.0300}
, number= {3}
, journal={ETRI Journal}
, publisher={Electronics and Telecommunications Research Institute}
, author={Rajkumar, Samikkannu
and
Senthilkumaran, V.N.
and
T, hiruvengadam}
, year={2015}
, month={May}
TY - JOUR
T2 - ETRI Journal
AU - Rajkumar, Samikkannu
AU - Senthilkumaran, V.N.
AU - T, hiruvengadam
SN - 1225-6463
TI - Outage Analysis of OFDM-Based Cognitive AF Relay Network in the Presence of Narrowband Interference
VL - 37
PB - Electronics and Telecommunications Research Institute
DO - 10.4218/etrij.15.0114.0300
PY - 2015
UR - http://dx.doi.org/10.4218/etrij.15.0114.0300
ER -
Rajkumar, S.
,
Senthilkumaran, V. N.
,
&
T, H.
( 2015).
Outage Analysis of OFDM-Based Cognitive AF Relay Network in the Presence of Narrowband Interference.
ETRI Journal,
37
(3)
Electronics and Telecommunications Research Institute.
doi:10.4218/etrij.15.0114.0300
Rajkumar, S
,
Senthilkumaran, VN
,
&
T, H
2015,
Outage Analysis of OFDM-Based Cognitive AF Relay Network in the Presence of Narrowband Interference,
ETRI Journal,
vol. 3,
no. 3,
Retrieved from http://dx.doi.org/10.4218/etrij.15.0114.0300
[1]
S Rajkumar
,
VN Senthilkumaran
,
and
H T
,
“Outage Analysis of OFDM-Based Cognitive AF Relay Network in the Presence of Narrowband Interference”,
ETRI Journal,
vol. 3,
no. 3,
May
2015.
Rajkumar, Samikkannu
and
,
Senthilkumaran, V.N.
and
,
T, hiruvengadam
and
,
“Outage Analysis of OFDM-Based Cognitive AF Relay Network in the Presence of Narrowband Interference”
ETRI Journal,
3.
3
2015:
Rajkumar, S
,
Senthilkumaran, VN
,
T, H
Outage Analysis of OFDM-Based Cognitive AF Relay Network in the Presence of Narrowband Interference.
ETRI Journal
[Internet].
2015.
May ;
3
(3)
Available from http://dx.doi.org/10.4218/etrij.15.0114.0300
Rajkumar, Samikkannu
,
Senthilkumaran, V.N.
,
and
T, hiruvengadam
,
“Outage Analysis of OFDM-Based Cognitive AF Relay Network in the Presence of Narrowband Interference.”
ETRI Journal
3
no.3
()
May,
2015):
http://dx.doi.org/10.4218/etrij.15.0114.0300