Cooperative overlay secondary transmissions exploiting primary retransmissions
 Samuel Baraldi Mafra^{1}Email author,
 Richard Demo Souza^{1},
 João Luiz Rebelatto^{1},
 Evelio MG Fernandez^{2} and
 Hirley Alves^{1, 3}
https://doi.org/10.1186/168714992013196
© Mafra et al.; licensee Springer. 2013
Received: 6 May 2013
Accepted: 10 July 2013
Published: 18 July 2013
Abstract
We introduce an overlay cooperative cognitive radio scheme, in which the secondary network transmits only during the retransmissions of the primary network. The secondary network makes use of multiple relays in order to increase its performance compared to a noncooperative scenario. Moreover, the secondary operates without harming the performance of the primary network. Different cooperative protocols are employed and associated with hybrid automatic repeat request mechanisms. Our results show that the incremental decodeandforward technique allows the secondary network to achieve the highest throughput among the considered methods, at the cost of a very small degradation in the performance of the primary network.
1 Introduction
Cognitive radio was introduced by Mitola and Maguire[1] to designate adaptive and intelligent communication devices, which can learn about its surroundings. Later, Haykin[2] defined cognitive radio as an intelligent wireless communication system able to adapt certain parameters (such as transmit power, carrier frequency, etc.) in order to provide highly reliable communications and efficient utilization of the radio spectrum. Furthermore, cognitive radio protocols can be divided into interweave, underlay, and overlay[3, 4]. In the interweave protocol, the unlicensed users (also referred to as secondary users) monitor the radio spectrum and communicate over spectrum holes without causing interference to the licensed users (or primary users). In the underlay protocol, the secondary users are allowed to transmit simultaneously to the primary users whereas the interference they cause is below a given threshold[5–7].
In the overlay cognitive radio protocol, the secondary users know, a priori, the primary user message. With this knowledge and using advanced signal processing techniques[8, 9], the secondary can transmit concurrently with the primary, without considerably harming its performance[4]. In[10], the authors proposed an overlay cognitive radio protocol in which the secondary exploits the primary retransmissions. The proposal in[10] is based on the fact that in many cases, there is an excess of mutual information after a retransmission with respect to the minimum mutual information required by the primary receiver to correctly decode the message. Then, during the retransmission, the primary link can tolerate a certain amount of interference without losing performance. Nevertheless, it is still of importance that this interference is kept to a minimum, confined to the excess mutual information in the primary link. However, in[10], the secondary interference may exceed the limit imposed by the excess of mutual information in the primary link, and the authors proposed a solution to eliminate this interference which requires global channel knowledge at the secondary transmitter (secondarysecondary, secondaryprimary, and primaryprimary channels). However, such global channel knowledge is much difficult to be obtained in practice. In[11], it is considered a similar scenario, but assuming that the nodes in the secondary network are provided with multiple antennas, which enables to considerably decrease the interference on the primary, without the need of global channel knowledge. However, this strategy may not be applied in situations where the size or cost of the devices limit the installation of multiple antennas.
An alternative to multiple antennas is to consider cooperative communications[12–14], where one or more nodes help the communication between source and destination by acting as relays, achieving spatial diversity even in a network composed of single antenna devices. In[12], the authors introduce the cooperative decodeandforward (DF) protocol and its selective (SDF) and incremental (IDF) variants. In the SDF protocol, the message is forwarded only if its decoding at the relay was successful. Finally, in the IDF protocol, similarly to the SDF protocol, the message also needs to be correctly decoded by the relay; however, the forwarding occurs only when requested by the destination. The higher the number of relays available for cooperation, the higher is the performance of the aforementioned cooperative protocols if an appropriate strategy is adopted such as best relay selection[15].
1.1 Contribution
We consider the same overlay cognitive radio scenario as in[10, 11], but including a cooperative secondary network with multiple relays, while the methods in[10, 11] consider a noncooperative secondary network. We investigate the performance of both the primary and the secondary networks in terms of throughput. In our proposed scheme, we consider the use of the SDF and IDF protocols, where the secondary destination combines the messages received from the secondary transmitter and from the relay by means of maximal ratio combining (MRC). In this work, our aim is to show that, while considering a cognitive radio protocol as that in[10], the proposed cooperative secondary network exploiting primary retransmissions is able to transmit at nonnegligible rates while causing practically no harm to the primary communications, without requiring global CSI. Moreover, the proposed cooperative secondary network is shown, through numerical and analytical results, to perform considerably better in terms of achievable rate as well as in terms of protecting the primary communications than the noncooperative secondary network proposed in[10].
The remainder of this paper is organized as follows. Section 2 describes the system model. The proposed scheme is introduced and analysed in Section 3. Section 4 presents some analytical and numerical results, while Section 5 concludes the paper.
2 System model
We consider a primary network composed of a transmitter T_{ p } and a destination D_{ p }. The secondary network consists of a secondary transmitter T_{ s }, a secondary destination D_{ s }, and N potentially cooperating relays denoted as r(l), with l ∈ Λ = {1,2,…,N}. The N relays are considered to be in a cluster, so that they are assumed to be at approximately the same position. The simplifying assumption that the relays are organized within a cluster is commonly utilized in the literature and can represent a number of practical scenarios (please see, for instance,[16–20]). The channel between any transmitter i and receiver j is denoted by h_{ ij } and follows a Nakagamim distribution[21] with fading parameter m_{ ij } and average power λ_{ ij }. The Nakagamim distribution is a general approach that includes the Rayleigh distribution as a special case (when m = 1). Moreover, through this model, the severity of the fading can be adjusted by the parameter m. Based on experimental results reported in[22], in this paper, we consider values of m = 1 and m = 2 for characterizing nonlineofsight (NLOS) and some lineofsight (LOS) scenarios.
where P_{ i } is the transmit power, x_{ i } is the transmitted message, and z_{ j } is additive white Gaussian noise with variance$\frac{{N}_{0}}{2}$ per dimension, where N_{0} is the unilateral noise power spectral density, which is assumed to be N_{0} = 1 W/Hz.
3 Proposed scheme
The proposed overlay cooperative cognitive radio scheme is based on the exploitation of retransmissions from the primary network. If a given primary transmission fails and the primary receiver requests a retransmission, then it is very likely that after a second transmission from the primary, the accumulated mutual information seen at the primary receiver is above the attempted primary rate, so that there may be an ‘excess of mutual information’ in the primary link[10]. If the attempted primary rate is R_{ p } and the accumulated mutual information at the primary receiver after a retransmission is I_{p,2} > R_{ p }, then the excess of mutual information is I_{p,2} − R_{ p }. This means that the primary network could tolerate some amount of interference without losing performance, therefore providing a margin for the secondary network operation.
Moreover, we assume that the secondary network only operates during a primary retransmission if D_{ s } was able to decode the original primary transmission from T_{ p }. That is because in this case, D_{ s } would be able to remove the primary interference during the primary retransmission, without requiring T_{ s } to make use of complex transmission techniques, such as dirty paper coding[26], nor requiring global channel knowledge. Note also that D_{ s } must inform T_{ s } that it could decode the original primary transmission, so that T_{ s } becomes aware of the secondary transmission opportunity. This can be done either through the main channel or through a dedicated low rate control channel.
i.e., the relay chosen to cooperate will be the one with the best channel condition with respect to D_{ s } among those that could decode the messages from both T_{ p } and T_{ s }. Hereafter, we will refer to the selected relay only as r. Note that the selected relay is chosen based only on the quality of the link between the relay and the destination. That is sufficient, as the relay is selected, only among those relays that were able to decode the source message.
A practical way to choose the best relay is to make each relay wait before transmitting for a time inversely proportional to its instantaneous channel state with respect to D_{ s }. Thus, in order to avoid collisions, the relay with the best condition will be the first to transmit while the others remain silent when perceiving a busy channel[15]. If none relay decoded the messages from T_{ p } and T_{ s }, then all relays remain silent. Additionally, since r could decode the original primary transmission, then it can eliminate the primary interference during the retransmission. Finally, as we consider a cooperative secondary network based on halfduplex nodes, the secondary transmissions occur in two time slots. As the secondary network only operates during the retransmission of the primary network, each time slot in the secondary network has half the duration of a time slot in the primary network.
In summary, the operation of the proposed cooperative cognitive network is as follows:

The primary transmitter T_{ p } sends a new message to the primary receiver D_{ p };

If the message was successfully received, then D_{ p } sends back an ACK signal to T_{ p }, otherwise a NACK is sent back;

In case a NACK is sent by D_{ p }, then the secondary receiver D_{ s } informs the secondary transmitter T_{ s } if it could decode the primary message or not;

If D_{ s } decoded the primary message, then a transmission opportunity is opened for the secondary transmitter T_{ s }, which then transmits concurrently to T_{ p } during the primary retransmission;

The transmission from T_{ s } lasts for only half the duration of the primary retransmission. During the second half of the primary retransmission, the selected relay r may forward or not to D_{ s } the message sent by T_{ s };

If the secondary network is operating under the SDF protocol, then r only forwards the message to D_{ s } if it could decode the message;

If the secondary network is operating under the IDF protocol, then r only forwards the message to D_{ s } if it could decode the message and if D_{ s } requested so. If not requested, then T_{ s } can send a new message in the second half of the primary time slot.
In what follows, we derive the throughput of the primary and secondary networks considering the proposed scheme.
3.1 Primary throughput
where$\gamma (a,b)={\int}_{0}^{b}{y}^{a1}exp(y)\mathit{\text{dy}}$ and$\mathrm{\Gamma}(a)={\int}_{0}^{\infty}{y}^{a1}exp(y)\mathit{\text{dy}}$ are, respectively, the lower incomplete Gamma function and the complete Gamma function[27, 28].
and the derivation is detailed in Appendix 1. Notice that$\text{Pr}\{\overline{{U}_{n}}\}=1\text{Pr}\{{U}_{n}\}$.
The term (A) in Eq. (6) is the probability that D_{ p } did not decode the message transmitted by T_{ p } after the retransmission, given that D_{ s } correctly decoded the primary message and at least one relay decoded both primary and secondary messages. The term (B) in Eq. (6) represents the probability that D_{ p } did not recover the message transmitted by T_{ p } after the retransmission, given that D_{ s } correctly decoded the primary message but no relay was able to decode both T_{ p } and T_{ s } messages, so that the secondary network operates in a noncooperative fashion. Finally, the term (C) in Eq. (6) is the probability that an outage occurred in the primary link after two transmissions, given that D_{ s } failed to decode the message from T_{ p }.
Refer to Appendix 2 for further details.
in which we used Bayes’ theorem and the fact that I_{p,2} ≥ I_{p,1}.
3.2 Secondary throughput
Now, we analyze the throughput of the secondary network using both SDF and IDF protocols. We assume that r forwards the message transmitted by T_{ s }. Upon receiving two copies of the same message (from T_{ s } and r), we consider that D_{ s } performs MRC. Recall that the secondary network only operates if the initial primary transmission failed and if the secondary transmitter was able to decode the primary message.
corresponds to the outage probability at D_{ s } given that T_{ s } and r cooperate and that their messages are combined at the destination. Closedform outage probability expressions for Eq. (13) are given in Appendix 3 for two different cases, when there is some LOS (m = 2) and under NLOS condition (m = 1).
The fragment (A) in Eq. (11) refers to the case where the secondary message is successfully delivered over the secondary direct link between T_{ s } and D_{ s }. The product${\mathcal{O}}_{p,1}\overline{{\mathcal{O}}_{\mathit{\text{ps}}}}$ accounts for the fact that there must have happened an outage in the previous primary transmissions (${\mathcal{O}}_{p,1}$) and that D_{ s } was able to decode the primary message ($\overline{{\mathcal{O}}_{\mathit{\text{ps}}}}$). The term$\overline{{\mathcal{O}}_{\mathit{\text{ss}}}}$ is the probability that the secondary direct link is not in outage. Moreover, the fragment (B) of Eq. (11) considers the case in which the secondary direct link is in outage but the secondary cooperative link is not. Again, the terms${\mathcal{O}}_{p,1}\overline{{\mathcal{O}}_{\mathit{\text{ps}}}}$ are the probability that the primary link was in outage in the previous transmission and that D_{ s } was able to decode the source message. As already mentioned, the term${\mathcal{O}}_{\mathit{\text{ss}}}$ is the probability that the secondary direct link (between T_{ s } and D_{ s }) is in outage, while$\text{Pr}\{\overline{{U}_{n}}\}$ is the probability that at least one relay is able to cooperate. The expression$\left(1\frac{{\mathcal{O}}_{\text{MRC}}}{{\mathcal{O}}_{\mathit{\text{ss}}}}\right)$ is the probability that the secondary cooperative link (the one formed by the combination of the transmissions from T_{ s } and from the selected relay r) is not in outage given that the direct link is in outage. Finally, the maximum achievable throughput at the secondary network using the SDF protocol is$\frac{{R}_{s}}{2}$, since the message is transmitted using two time slots.
Note that in this case, the only difference is that the maximum throughput in the secondary network is R_{ s }, since the selected relay only cooperates if requested by D_{ s }, so that it is possible to deliver a message in a single time slot if the secondary direct link is not in outage.
4 Numerical results
This section presents some numerical results in order to investigate the performance of the proposed cognitive cooperative scheme. Monte Carlo simulations are represented using black square markers and are included to demonstrate the accuracy of the analytical derivations. Moreover, we consider a pathloss exponent of α = 4, d_{ sp } ≈ d_{ rp }, d_{ ps } ≈ d_{ pr }, and d_{ sr } = d_{ ss }/2 (relay is positioned halfway between T_{ s } and D_{ s }). The distances in the network are normalized with respect to d_{ pp } = 1. Finally, we assume that T_{ s } and r transmit with the same power P_{ s }.
It can be seen that the proposed scheme presents a better performance, achieving a throughput of up to 0.55 bpcu without significantly harming the primary. The IDFbased proposed cooperative scheme outperforms the noncooperative scheme proposed in[10] for the whole range. Since the IDFbased proposed protocol presents a higher throughput than the SDFbased protocol, thus henceforth we only consider the IDFbased scheme.
From Figure7, we observe that when P_{ s } = −16 dB, the secondary throughput is increased from 1.06 to 1.60 bpcu when the number of available relays is increased from N = 1 to N = 4. In these conditions, the secondary network can even outperform the primary network in terms of throughput.
Finally, it is important to point out that if the secondary network is much closer to the D_{ p } than to T_{ p }, both schemes (the proposed scheme and the one in[10]) do not perform well once the secondary achieves very low throughput and degrades the primary network performance. We recall that as discussed above, the proposed scheme considerably outperforms the method introduced in[10], and even larger gains can be obtained if a larger number of relays is available.
5 Conclusions
This paper introduces a new cooperative transmission scheme for overlay cognitive radio in which the secondary network exploits the primary retransmissions. We show that the throughput of the secondary network can be significantly increased with a very small performance loss imposed to the primary network. Selective and incremental decodeandforwardbased cooperative protocols were analysed as well as the impact of having multiple available relays. Our results show that the best configuration for the proposed scheme is when the secondary nodes are close to each other and nearby the primary transmitter, a situation in which the secondary network can achieve relatively high throughput without damaging the performance of the primary network.
Appendices
Appendix 1 Probability of event U_{ n }
The final form of Pr{U_{ n }} as in Eq. (8) is attained by putting Eq. (15) and Eq. (16) into Eq. (17). Note that Pr{U_{ n }} tends to zero as the number of relays N increases.
Appendix 2 Outage probability${\mathcal{O}}_{p,2}$
where${\sigma}_{p}^{2}=max\left[{\sigma}_{s}^{2},{\sigma}_{r}^{2}\right]$.
Finally, the complete outage probability${\mathcal{O}}_{p,2}$ is given by the sum of Eqs. (23), (25), and (26), as given in Eq. (9). The accuracy of the derived closedform expressions is investigated in Section 4.
Appendix 3 Outage probability${\mathcal{O}}_{\mathbf{\text{MRC}}}$
Declarations
Acknowledgements
This paper was partially presented at The Ninth International Symposium on Wireless Communication Systems (ISWCS), Paris, 2012. The authors would like to thank the support by CAPES and CNPq, Brazil, and Infotech Oulu, Finland.
Authors’ Affiliations
References
 Mitola J, Maguire GQ: Cognitive radio: making software radios more personal. IEEE Pers. Commun. 1999, 6(4):1318. 10.1109/98.788210View ArticleGoogle Scholar
 Haykin S: Cognitive radio: brainempowered wireless communications. IEEE. J. Sel. Areas Commun. 2005, 23(2):201220.View ArticleGoogle Scholar
 Goldsmith A, Jafar S, Maric I, Srinivasa S: Breaking spectrum gridlock with cognitive radios: an information theoretic perspective. Proc. IEEE, 2009, 97(5):894914.View ArticleGoogle Scholar
 Srinivasa S, Jafar SA: The throughput potential of cognitive radio: a theoretical perspective. IEEE Commun. Mag. 2007, 45(5):7379.View ArticleGoogle Scholar
 da Costa DB, Aissa S, Cavalcante CC: Performance analysis of partial relay selection in cooperative spectrum sharing systems. Wireless Person. Commun. 2012, 64(1):7992. 10.1007/s1127701205185View ArticleGoogle Scholar
 Duong TQ, da Costa DB, Tsiftsis TA, Zhong C, Nallanathan A: Outage and diversity of cognitive relaying systems under spectrum sharing environments in Nakagamim fading. IEEE Commun. Lett. 2012, 16(12):20752078.View ArticleGoogle Scholar
 Duong TQ, da Costa DB, Elkashlan M, QBao VN: Cognitive amplifyandforward relay networks over Nakagamim Fading. IEEE Trans. Veh. Techol. 2012, 61(5):23682374.View ArticleGoogle Scholar
 Jovicic A, Viswanath P: Cognitive radio: an information theoretic perspective. IEEE Trans. Inf. Theory 2009, 55(9):39453958.MathSciNetView ArticleGoogle Scholar
 Pereira RC, Souza RD, Pellenz ME: Multiple concurrent transmissions in wireless mesh networks employing superposition and dirty paper coding. IEEE Trans. Veh. Technol. 2009, 58(9):51155123.View ArticleGoogle Scholar
 Tannious RA, Nosratinia A: Cognitive radio protocols based on exploiting hybrid ARQ retransmissions. IEEE Trans. Wireless Commun. 2010, 9(9):28332841.View ArticleGoogle Scholar
 Souza RD: Reducing coexistence penalty of retransmissionbased cognitive radio protocol. IEE Electron. Lett. 2011, 47(6):409411. 10.1049/el.2010.3300MathSciNetView ArticleGoogle Scholar
 Laneman JN, Tse DNC, Wornell GW: Cooperative diversity in wireless networks: efficient protocols and outage behavior. IEEE Trans. Inf. Theory 2004, 50(12):30623080. 10.1109/TIT.2004.838089MathSciNetView ArticleMATHGoogle Scholar
 Sendonaris A, Erkip E, Aazhang B: User cooperation diversity. Part I. System description. IEEE Trans. Commun. 2003, 51(11):19271938. 10.1109/TCOMM.2003.818096View ArticleGoogle Scholar
 Nosratinia A, Hunter TE, Hedayat A: Cooperative communication in wireless networks. IEEE Commun. Mag. 2004, 42(10):7480. 10.1109/MCOM.2004.1341264View ArticleGoogle Scholar
 Bletsas A, Khisti A, Reed DP, Lippman A: A simple cooperative diversity method based network path selection. IEEE J. Select. Areas Commun. 2006, 24: 659672.View ArticleGoogle Scholar
 Krikidis I, Thompson J, McLaughlin JS, Goertz N: Amplifyandforward with partial relay selection. IEEE Commun. Letters 2008, 12(4):235237.View ArticleGoogle Scholar
 Duong TQ, Zepernick H: Hybrid decodeamplifyforward cooperative communications with multiple relays. In IEEE Wireless Communications and Networking Conference. Budapest; 5–8 April 2009:16.Google Scholar
 da Costa DB, Aissa S: Performance analysis of relay selection techniques with clustered fixedgain relays. IEEE Signal Proc. Lett. 2010, 17(2):201204.View ArticleGoogle Scholar
 Krikidis I, Charalambous T, Thompson JS: Bufferaided relay selection for cooperative diversity systems without delay constraints. IEEE Trans. Wireless Commun. 2012, 11(5):19571967.View ArticleGoogle Scholar
 Ferdinand NS, Jayasinghe U, Rajatheva N, Latvaaho M: Impact of antenna correlation on the performance of partial relay selection. EURASIP J Wireless Commun. Netw 2012, 2012: 113. 10.1186/1687149920121View ArticleGoogle Scholar
 Nakagami N: The mdistribution, a general formula for intensity distribution of rapid fading. In Statistical Methods in Radio Wave Propagation. Edited by: W. G. Hoffman, W. G. Hoffman . Pergamon,Oxford; 1960.Google Scholar
 Yacoub MD: The κ − μ distribution and the η − μ distribution. IEEE Antennas Propagation Mag. 2007, 49(1):6881.View ArticleGoogle Scholar
 Goldsmith A: Wireless Communications. New York, NY: Cambridge University Press; 2005.View ArticleGoogle Scholar
 Knopp R, Humblet P: On coding for block fading channels. IEEE Trans. Inf. Theory 2000, 46(1):189205. 10.1109/18.817517View ArticleMATHGoogle Scholar
 Biglieri E, Caire G, Taricco G: Limiting performance of blockfading channels with multiple antennas. IEEE Trans. Inf. Theory 2001, 47(4):12731289. 10.1109/18.923715MathSciNetView ArticleMATHGoogle Scholar
 Costa MHM: Writing on dirty paper (Corresp.). IEEE Trans. Inf. Theory 1983, 29(3):439441. 10.1109/TIT.1983.1056659View ArticleMATHGoogle Scholar
 Wang Z, Giannakis G: A simple and general parameterization quantifying performance in fading channels. IEEE Trans. Commun 2003, 51(8):13891398. 10.1109/TCOMM.2003.815053View ArticleGoogle Scholar
 Savazzi S, Spagnolini U: Cooperative spacetime coded transmissions in Nakagamim fading channels. In IEEE Global Telecommunications Conference. Washington, DC; 26–30 November 2007:43344338.Google Scholar
 Kim H, Lim S, Wang H, Hong D: Optimal power allocation and outage analysis for cognitive full duplex relay systems. IEEE Trans. Wireless Commun. 2012, 11(10):37543765.View ArticleGoogle Scholar
 Punchihewa A, Bhargava VK, Despins C: Capacity and power allocation for cognitive MAC with imperfect channel estimation. IEEE Trans. Wireless Commun. 2011, 10(12):40014007.View ArticleGoogle Scholar
 Pei E, Wang S, Zhang Z: Capacity and optimal power allocation for spectrumsharing with primary transmission consideration in fading channels. IEEE Commun. Lett. 2011, 15(4):389391.View ArticleGoogle Scholar
 Gong X, Vorobyov SA, Tellambura C: Optimal bandwidth and power allocation for sum ergodic capacity under fading channels in cognitive radio networks. IEEE Trans. Signal Proc. 2011, 59(4):18141826.MathSciNetView ArticleGoogle Scholar
Copyright
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.