Resource allocation for multicarrier cooperative cognitive radio networks with imperfect channel state information

Hecke, Jeroen Van; Fiorentino, Paolo Del; Giannetti, Filippo; Lottici, Vincenzo; Vandendorpe, Luc; Moeneclaey, Marc

doi:10.1109/pimrc.2014.7136246

Cited by 4 publications

(5 citation statements)

References 17 publications

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“…where f is the minimum mean-squared error (MMSE) estimate of f based on ICSI, and the estimation error e is independent of f . For the numerical results we will make some additional assumptions about ICSI as in [16]. We consider the case where the channel f (t) is slowly time-varying.…”

Section: Appendix B Imperfect Csimentioning

confidence: 99%

“…This paper addresses the design of a distributed resource allocation (RA) algorithm which minimizes the exact outage probability of a single-carrier SU network based on multi-antenna RNs operating in an amplifyand-forward (AF) mode in an underlay scenario. Our aim, is to extend our previous works [16]- [18] by considering fixed RNs equipped with multiple transmit and receive antennas. More specifically, first we show that the optimal CB matrix at the RN, considered in [12], [15], can be reduced to a CB vector.…”

Section: Introductionmentioning

confidence: 99%

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Distributed Dynamic Resource Allocation for Cooperative Cognitive Radio Networks With Multi-Antenna Relay Selection

Hecke

Fiorentino

Lottici

et al. 2017

IEEE Trans. Wireless Commun.

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A cognitive radio scenario is considered where the signals transmitted by a secondary user (SU) are relayed by multi-antenna relays using an amplify-and-forward cooperation protocol. In this paper, the optimal power allocation and beamforming scheme is derived for the SU transmitters (SU-TXs) which minimizes the exact outage probability of the SU network with relay selection, under both a transmit power constraint and a constraint on the interference power generated at every primary user receiver. After deriving the optimal structure of the beamforming matrix, several distributed resource allocation algorithms are obtained for different levels of channel state information (CSI) at the SU-TXs: perfect CSI and imperfect CSI are considered, along with the case where only channel distribution information (CDI) is available. The numerical results show that the multi-antenna relays can significantly improve the performance of the SU network, which would otherwise be severely limited by the harsh interference constraints. Further, we also investigate how the number of relays, the number of antennas and the level of CSI impact the performance of the SU network. Finally, we point out that the proposed algorithms outperform several algorithms presented in literature.

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Section: Appendix B Imperfect Csimentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Distributed Dynamic Resource Allocation for Cooperative Cognitive Radio Networks With Multi-Antenna Relay Selection

Hecke

Fiorentino

Lottici

et al. 2017

IEEE Trans. Wireless Commun.

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“…In fact, perfect CSI in RA problem [43][44][45] cannot be obtained because of channel delays and hardware limitation in channel estimation. In Section 3.2.3, we will describe the channel estimation of () in detail.…”

Section: Interference Vectormentioning

confidence: 99%

Spectral Efficiency Analysis of Filter Bank Multi‐Carrier (FBMC)‐ Based 5G Networks with Estimated Channel State Information (CSI)

Zhang¹,

Lv²,

Li³

2016

Towards 5G Wireless Networks - A Physical Layer Perspective

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Filter bank multi-carrier (FBMC) modulation, as a potential candidate for physical data communication in the fifth generation (5G) wireless networks, has been widely investigated. This chapter focuses on the spectral efficiency analysis of FBMC-based cognitive radio (CR) systems, and spectral efficiency comparison is conducted with another three types of multi-carrier modulations: orthogonal frequency division multiplexing (OFDM), generalized frequency division multiplexing (GFDM), and universal-filtered multi-carrier (UFMC). In order to well evaluate and compare the spectral efficiency, we propose two resource allocation (RA) algorithms for single-cell and two-cell CR systems, respectively. In the single-cell system, the RA algorithm is divided into two sequential steps, which incorporate subcarrier assignment and power allocation. In the two-cell system, a noncooperative game is formulated and the multiple access channel (MAC) technique assists to solve the RA problem. The channel state information (CSI) between CR users and licensed users cannot be precisely known in practice, and thus, an estimated CSI is considered by defining a prescribed outage probability of licensed systems. Numerical results show that FBMC can achieve the highest channel capacity compared with another three waveforms.

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“…The transmitter will then use the previous P channel estimates to make a linear minimum-mean-square-error (MMSE) prediction ĥ of the channel. This predicted channel ĥ is linked to the actual channel h(i) as follows [14]:…”

Section: Channel Modelmentioning

confidence: 99%

“…Second, a novel relay selection criterion based on the GP metric is introduced. Third, our link performance prediction (LPP) combines the ESM method [13] with outdated and imperfect CSI at the transmitter [14], in order to obtain the predicted GP (PGP). This PGP function represents the objective function of our RA problem.…”

Section: Introductionmentioning

confidence: 99%

Goodput-maximizing resource allocation in cognitive Radio BIC-OFDM systems with DF relay selection

Hecke

Fiorentino

Andreotti

et al. 2015

2015 IEEE International Conference on Communications (ICC)

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We propose a novel resource allocation (RA) strategy for a cognitive radio packet-oriented bit-interleaved coded orthogonal frequency division multiplexing (BIC-OFDM) system with decode-and-forward (DF) relays. The aim of the RA is maximizing the goodput (GP) of the source-relay-destination link, which is the number of information bits correctly received at the destination node per unit of time. Therefore, we derive an accurate analytic approximation for this figure of merit, which allows us to find the optimum constellation size, code rate and energy allocation per subcarrier. Further, this expression also serves as a novel relay selection criterion. Finally, we validate the proposed RA method, and compare its performance to capacitymaximizing algorithms through numerical simulations

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Resource allocation for multicarrier cooperative cognitive radio networks with imperfect channel state information

Cited by 4 publications

References 17 publications

Distributed Dynamic Resource Allocation for Cooperative Cognitive Radio Networks With Multi-Antenna Relay Selection

Distributed Dynamic Resource Allocation for Cooperative Cognitive Radio Networks With Multi-Antenna Relay Selection

Spectral Efficiency Analysis of Filter Bank Multi‐Carrier (FBMC)‐ Based 5G Networks with Estimated Channel State Information (CSI)

Goodput-maximizing resource allocation in cognitive Radio BIC-OFDM systems with DF relay selection

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