DSpace at VNU: Efficient re-use of CRs under deep fading for improving cooperative sensing performance

Efficient Re-use of CRs under Deep Fading for Improving Cooperative Sensing Performance Dinh Thi Thai Mai, Nguyen Quoc Tuan Dinh-Thong Nguyen University of Engineering and Technology, Vietnam National University, Hanoi - Vietnam Faculty of Engineering and Information Technology, University of Technology, Sydney – Australia Email: dinh-thong-nguyen@eng.uts.edu.au Email: dttmai@vnu.edu.vn, tuannq@vnu.edu.vn In most current research publications on cooperative spectrum sensing using CRs, the wireless links between individual CRs and the fusion centre, i.e the reporting channels, are assumed lossless In reality, when these channels are of significant distance in suburban macrocells or under shadowing in urban microcells, loss and fading is a significant issue Cooperative diversity relaying has become a popular research topic for combating serious fading problems Once a channel is in deep fade, advanced message coding is no longer effective in improving transmission reliability, and cooperative diversity transmission has proved to dramatically improve the performance of wireless transmission In most practical situations, a wireless channel is non-ergodic and its capacity is a random variable, thus no transmission rate is reliable In this case, the outage probability is defined as the probability that the instantaneous random capacity falls below a given threshold, and capacity versus outage probability is the natural information theoretic performance measure [6] The cooperative diversity relay can process the information it receives from the source and forward the information to the destination using either amplify-and-forward (AF) or decodeand-forward (DF) protocols Abstract – It is well known in the research field of cooperative spectrum sensing that deeply faded local cognitive sensors need to be eliminated from contributing to the fusion pool at the fusion center in order to improve global detection reliability Also, most current works on the topic unrealistically assume that the reporting channels between the cognitive sensors and the fusion center are free of loss and fading This paper proposes an innovative technique to re-use those eliminated sensors by reassigning them to act as cooperative diversity relays to assist the surviving sensors in combatting outages due to Rayleigh fading in the reporting channel I INTRODUCTION Cooperative spectrum sensing using cognitive radios (CRs) has become a popular technique in sensing a primary user under a multipath fading and/or shadowing environment [1] [2] The sensing is done in two stages: in the sensing stage, the CRs independently measure and process the signal from the primary user, and in the reporting stage the CRs independently report the processed information to a fusion center (FC) which is usually a cognitive base station, to make the final global sensing decision as to whether the primary user is present or absent Most researchers, however, not take into account the differences in local transmission quality and reliability between individual sensors Signal-to-noise ratio (SNR) is a dominant metric of transmission quality affecting the detection performance of a CR sensor This is particularly true in the most common sensing technique using energy detection [3] [4] When the popular k-out-of-N decision fusion rule is used, it is easy to see that the inclusion of deeply faded CRs, i.e with low SNRs, in the decision fusion at the fusion center diminishes the reliability of the cooperative CR detection of the primary user In [5] the authors presented a deep fading scenario under correlative shadow fading and proved that by discarding the detection contribution from shadowed CRs, the detection probability of the centralized cooperative CR network was improved The CRs under shadowing are therefore wasted In this paper, we are not interested in how to identify the unreliable or low quality CRs and how many are to be discarded from the fusion process, but only in how to re-use these CRs to assist channels between the CRs and the fusion center With the knowledge of the SNRs of the primary user’s signal received at indidual CRs, i.e SNRs of the sensing channels, the FC can use various algorithms to handle this issue 978-1-4577-0255-6/11/$26.00 ©2011 IEEE In this paper, we propose an efficient re-use of those CRs under deep fading of the sensing channels by re-assigning them to act as diversity relays to their more healthy peers in the reporting channels, thus improving the global detection reliability of the fusion center II COOPERATIVE SPECTRUM SENSING A Sensing System Definition Figure shows a cooperative spectrum sensing CR network in which local CRs detect signals from the primary user, perform local processing, then send their detected signals {yi, i=1, , N} to the fusion centre (FC) for the latter to make the final global sensing decision as to whether the primary user is absent ( Η ) or present ( Η1 ) In many applications, the CRs report their local {SNRi}and {PDi}to the fusion centre via the reporting wireless channels In this paper, for simplicity of analysis, we assume that reporting channels are subject to Rayleigh fading only, so that we can concentrate on the main theme, that is the principle of re-use of those CRs which are otherwise discarded from the cooperative sensing process by the fusion centre 479 TENCON 2011 chosen otherwise Under this rule the global average probabilities are B Detection and False Alarm Probabilities over Fading Channels There are two probabilities that are most commonly used as performance metrics for spectrum sensing: probability of a false alarm PF which is the probability that a signal is detected while it does not exist, and probability of detection PD which is the probability that the presence of a signal is correctly detected n QF = ∑ Γ(m, λ / 2) = Gm (λ ) Γ ( m) QD = n n ∑ ∑ ∏ ( PDi )u (1 − PDi )1−u i (6) i j = k ∑ ui = j i =1 Phenomenon (1) {H , H1} Sensing channel PD in fading conditions is obtained by averaging its value in the AWGN case over the SNR fading distribution f(γ), while PF remains the same under all fading conditions since it is calculated under Η hypothesis, i.e no signal, hence independent of SNR, i.e ∞ (5) and where λ is the power detection threshold, Γ(.) and Γ(.,.) are complete and incomplete gamma functions, respectively PD , fading = ∫ f (γ )Qm ( 2γ , Gm−1 ( PF )) d γ n u 1−u ∏ ( PFi ) i (1 − PFi ) i j = k ∑ ui = j i =1 Probabilities of false alarm is given in [1] as PF = P ⎡⎣Y > λ Η ⎤⎦ = ∑ dsr CR1 PD1 Reporting channel CR2 CRN PD2 … PDN dsd drd (2) Fusion Center Where γ is the SNR, Qm(.,.) is the generalized Marcum’s Q function of 2m degree of freedom δ i = ( PD , PF , SNRi ) i i The exponential pdf of SNR in a Rayleigh fading channel is f (γ ) = γ γ γ exp(− ) , u0 {0,1} (3) Figure : A decentralized cooperative spectrum sensing network with the Nth CR sensor eliminated from the fusion process By replacing (3) into (2), we obtain the average probability of detection of the local CR subject to Rayleigh fading [3] as P = D,Rayleigh III A Cooperative Relaying System Definition Figure shows a simple cooperative diversity relay network using M relaying branches The system definition below is taken from [8] In the application for CR reuse in this paper, a Source is a reliable CR, the Destination is the FC and a Relay is an unreliable CR being reused The relays are assumed to operate in the time division mode having two phases: the relay-receive phase and the relay-transmit phase; each phase or sub-block is of duration T/2 There is no correlation between the source transmit signal and the relay transmit signal Γ( m − 1, λ / 2) λ + exp( − )× Γ (m − 1) 2(1 + mγ ) ⎤ ⎡ ⎢1 + mγ ⎥ ⎣ ⎦ λ mγ ⎡ ⎤ ) m−1 ⎢ Γ( m − 1, 2(1 + mγ ) ⎥ ⎢1 − ⎥ Γ( m − 1) ⎢ ⎥ ⎢⎣ ⎥⎦ COOPERATIVE DIVERSITY RELAYING (4) The behavior of PD versus PF curve represents the receiver operating characteristics (ROC) C Cooperative Spectrum Sensing In this paper, we assume that individual CRs send their PDi, PFi, and received signal power SNRi, i.e a de-centralized case Note that these are {SNRi} of the sensing channels Let ui = [0,1], i=1,2,…,n, denote the 1-bit decision from the ith CR If the individual measurements are mutually independent, then the k-out-of-n rule is most popular by which hypothesis Η1 is chosen if k or more individual decisions are 1, and Η is In the relay-receive phase at discrete time m =1,2,…T/2, the source transmits the complete message of symbols to both the destination and the relays (broadcast mode) in the AF case, but only to the relays in the DF case, i.e only (7a) applies 480 ysri [m ] = PS [ m ]hsri xs [ m ] + nsri [ m] (7a) ysd [m] = Ps [m]hsd xs [m] + nsd [m] (7b) subject, in this paper the same as in [8], we simply use SNR to mean γAWGN In the decode-and-forward (DF) relaying protocol, the relay detects by fully decoding the entire codeword it receives from the source in the relay-receive phase, symbol by symbol, then retransmits the signal, after recoding it, to the destination during the relay-transmit phase Under Rayleigh fading, SNR in (9) is an independent exponential random variable with expected (average) value In the relay-transmit phase at discrete time m=T/2+1, T/2+2,….T, the relays send their signals to the destination and the source may or may not send signal to the destination depending on the relaying protocol used (multiple access mode) The received signal at the destination is γ ij = i =1 σ ij2 = μij SNR (10) t The outage probability, Phou ( μt h ) of the wireless link between ij two points i and j having instantaneous channel gain hij for a given outage information rate threshold, Rth is defined as M yrd [ m] = ∑ Pri hri d xri [m] + nri d [m] μij Pi (8) ysd [m] = Ps [k ]hsd xs [ m] + nsd [m] { Phout (SNR, Rth ) = Pr hij ij } < μth = Fh (μth ) ij (11) where the channel gain threshold is defined as μth = 2( M +1) Rth − SNR and M is the diversity order B Outage Probability of a Single Wireless Link Since the channel gain has the exponential distribution as in (3) with mean µij, the outage probability of the direct link between the source and the destination (without relaying), is simply Figure 2: Diagram of an M-relay cooperative diversity relaying network where x, y, n, and P are the normalized transmit signal, i.e E x = , the corresponding received signal, the additive ( ) Psdout ( μth ) = Fhsd ( μth ) = − e noise which is modeled as a circularly symmetric complex Gaussian random variable with zero mean and variance σ2 at the receiver, i.e n ~ N(0,σ2), and the transmit power, respectively The parameters’ double subscript ij is to mean being associated with the channel link from i to j hij is the channel gains (or loss) from node i to node j, being subject to frequency nonselective Rayleigh fading, and is modeled as independent, circularly symmetric, complex Gaussian random variables with zero mean and variance µij It is well known that under Rayleigh fading, hij γ ij = σ2 Pi is exponentially distributed = hij γ ijAWGN μ sd (12) C Outage Probability of Cooperative DF RelayingNetwork It is not the subject of this paper to study various cooperative diversity relaying protocols We choose to use the selection DF (SDF) relaying protocol as an example to demonstrate the benefit of sensors’ re-use in cooperative spectrum sensing in a deep fading environment In SDF relaying protocol, when the relay is not able to decode the source message, i.e the source-relay link is in outage, the source repeats its transmission to the destination on the direct link The maximum average information rate in this case, i.e first part of (13) is that of repetition coding The information rate of a selection DF relay network can be expressed as below [7] We define the instantaneous signal-to-noise ratio (SNR) in the received signal as hij μth ⎧ ⎪⎪ log (1 + 2γ sd ) I SDF = ⎨ ⎪ log(1 + γ + γ ) sd rd ⎪⎩ (9) ij where γ ijAWGN is the SNR of the unfaded AWGN channel γ sr < γ th (13) γ sr ≥ γ th In SDF relaying protocol, it is assumed that a reused CR has to have the knowledge of the CSI, i.e γsr, between itself and the For convenience, and to be consistent with many papers on the 481 CR that it assists Its outage probability under exponential fading condition is therefore [8] out PSDF ( μth ) = Pr( hSDF = Pr(2 hsd + Pr( hsr 2 μ ⎛ − th μ sd ⎜ = 1− e ⎜⎜ ⎝ + μ sd − μrd ≤ μth ) < μth ) + hrd < μth ) Pr( hsr ≥ μth ) Pr μ − th μsr e ({ h sd μ ⎞⎛ − th ⎟⎜1 − e μsr ⎟⎜ ⎟⎜ ⎠⎝ to improve the transmission reliability of the CR1-to-FC reporting channel, thus forming a 3-terminal relay network with the surviving CR1 as the source (S), the eliminated CRN as the relay (R) and the FC as the destination (D) It is expected that the outage probability in (15) is lower with the diversity gain by the use of the relay compared to that without the relay, hence improving the local effective probability of detection received by the fusion center }SNR2> >SNRN and the CRs are indexed in this same order Step 4: The FC sets a SNR threshold, SNRth, below which the corresponding probability of detection, Pi , is eliminated from contributing to the sensing fusion The MSNR2> .>SNRM-R>SNRM-R+1> >SNRM-1> SNRM > SNRth>SNRM+1 > >SNRM+R (15) • where Pout (i) is the outage probability of the channel between the ith CR by the FC • Step 5: Assume that we use all R discarded CRs as relays Assign CRM+1 to be the relay for CRM, CRM+2 for CRM1 and CRM+R for CRM-R-1 Step 6: Calculate outage probability of the direct link of out the surviving CRs, i.e PSD (i) (i=1,2, ,M), using (12) • • • • out Step 7: Calculate PSDF (i ) (i=M-R+1, M) of the resulting R cooperative diversity relay networks using SDF protocol in (14) Step 8: Calculate the local effective probability of detection {PDe(i)}(i=1,2, ,M) from (15) Step 9: Calculate the global probability of detection, QD, using (6) for with (in Step 7) and without (in Step 6) cooperative diversity relaying Step 10: Plot the ROC with and without using relays IV Figure 3: A simulation scenario of Cooperative Spectrum Sensing under a multipath fading and shadowing environment RESULTS AND CONCLUSIONS In Figure 3, we illustrate a fading scenario of the sensing channels from a TV station to the CRs some of which suffer from deep fading such as shadowing from trees and buildings, giving very low SNRs and consequently their local reported contributions are discarded by the fusion centre Again, the exact physical location of the CRs is not an issue in this paper; we assume for simplicity of the simulation that all CRs are approximately at equal distances to the cognitive base station We propose a method that utilizes eliminated CRs by assigning them to act as cooperative diversity relays for the surviving CRs that still stay in the fusion pool In Figure 1, we illustrate an example in which CRN suffers from deep fading and its reported information is discarded by the fusion center The fusion centre then reassigns CRN to act as a relay for CR1 482 (CRBS) and that the CRs are distributed at equal distances from one another Figures 4a and 4b show the simulation results of the receiver operating characteristic (ROC) curves of the cooperative sensing network in three operating environments: transparent reporting channels (no fading reporting channels without reuse of discarded CRs as diversity relays, and Rayleigh fading reporting channels with re-use of discarded CRs as diversity relays All ROC curves are for the case of three re-used CRs and the AND fusion rule is used for simplicity The outage channel gain threshold µth is much lower, i.e much healthier SNR, in Figure 4a than in Figure 4b giving much higher probability of detection, and therefore the benefit of re-use of deeply faded CRs is not as pronounced in Figure 4a compared to Figure 4b However, in both cases the benefit of the proposed re-use of poor sensing CRs as diversity relays is very convincing As in [8], we simulate a fading scenario of the sensing channels in which CRs 7,8,11,12 are subject to log-normal fading and the rest are under Rayleigh fading The SNRs in the raw signals measured at the 12 CRs are {SNRi}=[10, 9, 3, 7, 8, 9, -3, -6, 12, 6, 0.2, 1] dB, and the threshold set by the FC is SNRth=0.5 dB Thus the three CRs 8, and 11 are excluded from the decision fusion and reassigned to act as relays for CRs 10, and 12, respectively, in the reporting channels The resulting 3-node cooperative diversity relay networks are assumed to be subjected to exponential fading with realization mean parameters (µsd, µsr, µrd) = (0.01, 1, 0.01); (0.01, 0.1111, 0.01) ; (0.01, 0.04, 0.01) The idea proposed in this paper is innovative and many issues need to be investigated such as how to optimally determine the SNR threshold SNRth and how to optimally reassign the eliminated CRs to assist the surviving CRs in order to preserve the total power or to maximize the final probability of detection These issues are being investigated by our group ACKNOWLEDGEMENTS This work was supported by a research grant from QG.10.44 TRIGB and QC 09.28 Projects of the University of Engineering and Technology, Vietnam National University Hanoi REFERENCES [1] A Ghasemi and E.S Sousa, “Collaborative Spectrum Sensing for Opportunistic Access in Fading Environments,” Proc IEEE 1st Symposium on Dynamic Spectral Access Networks (DySPAN’05), pp 131-136, Baltimore, November 2005 [2] A Ghasemi and E.S Sousa, “Opportunistic Spectrum Access in Fading Channels Through Collaborative Sensing,” Journal of Communications, vol 2, No 2, pp 71-82 , March 2007 (a) [3] F.F Digham, M.S Alouini and M.K Simon, “On the energy detection of unknown signals over fading channels,” Proc IEEE Int Conf on Coms ICC’03, pp.3575-3579, May 2003 [4] Yi Zheng et al “Cooperative Spectrum Sensing Based on SNR Comparison in Fusion Center for Cognitive Radio,” Proc International Conference on Advanced Computer Control, ICACC’2009, pp 212-216, 22-24 Jan 2009 [5] DTT Mai et al “Improving Cooperative Spectrum Sensing under Correlated Log-normal Shadowing,” Proc International Conference Cyber 2010, October,2010 [6] L.H Ozarow et al., “Information theoretic considerations for cellular mobile radio,” IEEE Trans on Vehicular Technology, vol 43, no 2, pp.359377, May 1994 [7] J.N Laneman et al., “Cooperative Diversity in Wireless Networks: Efficient Protocols and Outage Behavior,” IEEE Trans Inform Theory, 50 (12), pp 3062-3080, Dec 2004 [8] D.T Nguyen et al “Outage Probability Analysis of Cooperative Diversity DF Relaying under Rayleigh Fading,” Submitted to ATC’11 International Conference, Aug 2011 (b) Figure 4: Sensing performance of the cooperative spectrum sensing network under fading with and without re-use of poor CRs as diversity relays, (a) Outage threshold µth =0.001 and (b) Outage threshold µth= 0.005 483 ... ⎟⎪ ⎟⎟ ⎬ ⎠ ⎪⎭ (14) • D Algorithm for Re-use of CRs in Cooperative Sensing under Deep Fading In cooperative spectrum sensing, a CR in deep fading will be eliminated from the fusion process by the... Analysis of Cooperative Diversity DF Relaying under Rayleigh Fading, ” Submitted to ATC’11 International Conference, Aug 2011 (b) Figure 4: Sensing performance of the cooperative spectrum sensing. .. repeats its transmission to the destination on the direct link The maximum average information rate in this case, i.e first part of (13) is that of repetition coding The information rate of a