STTC design for vehicular communication systems employing fixed‐gain AF PLNC over cascaded fading channels

Ata, Serdar Ozgur; Altunbaş, İbrahim

doi:10.1049/iet-com.2017.0702

Cited by 6 publications

(8 citation statements)

References 43 publications

(53 reference statements)

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“…The analysis of the performance of MIMO systems over double scattering channels is relatively scarce and is mainly represented by the works in [12]- [24]. Specifically, the performance of point-to-point MIMO system under double scattering channels has been studied in [12]- [19], where the authors in [12] showed that the required number of scatterers in the channel to achieve full diversity is the product of the number of transmit (Tx) antennas and receive (Rx) antennas. In [13], the optimal capacity-achieving beamforming directions under double scattering channels were studied in [13] and were proven to correspond to the eigenvectors of the transmit spatial correlation matrix, while a tight upper bound on the ergodic capacity was provided [14].…”

Section: A Prior Workmentioning

confidence: 99%

“…The authors in [17] derived the asymptotic variance of mutual information under Rayleigh product channels and characterized the tradeoff between multiplexing gain and diversity gain under the uniform power transmission. The authors in [19] investigated the error performance of vehicleto-vehicle communication systems undergo double Rayleigh fading considering physical-layer network coding and space-time trellis coding techniques.…”

Section: A Prior Workmentioning

confidence: 99%

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Asymptotic Analysis of MRT Over Double Scattering Channels With MMSE Estimation

Nadeem

Kammoun

Debbah

et al. 2020

IEEE Trans. Wireless Commun.

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This paper studies the ergodic rate performance of maximum ratio transmission (MRT) precoding in the downlink of a multiuser multiple-input single-output (MISO) system, where the channel between the base station (BS) and each user is modeled using the double scattering model. We utilize the minimum-mean-square-error (MMSE) channel estimate for this model, which is used in the design of the MRT precoding. Within this setting, we are interested in deriving tight approximations of the ergodic rate under the assumption that the number of BS antennas (N), the number of users (K) and that of scatterers (S) grow large with the same pace. These approximations are expressed in simplified closedform expressions for the special case of multi-keyhole channels. They reveal that unlike the standard Rayleigh channel in which the SINR grows as O N K , the SINR associated with a multi-keyhole channel scales as O S K. This particularly shows that the reaped gains of the large-scale MIMO over double scattering channels do not linearly increase with the number of antennas and are limited by the number of scatterers. We further provide simulation results that confirm the close match provided by the asymptotic analysis for moderate system dimensions and provide some useful insights into the interplay between N , K and S.

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Section: A Prior Workmentioning

confidence: 99%

Section: A Prior Workmentioning

confidence: 99%

Asymptotic Analysis of MRT Over Double Scattering Channels With MMSE Estimation

Nadeem

Kammoun

Debbah

et al. 2020

IEEE Trans. Wireless Commun.

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“…Because of the complex function operation in (26), there is no closed solution. When N t = 1, the closed-form expressions of (26) is given as…”

Section: The Probability Of Spsc For the Optimal And Suboptimal Tmentioning

confidence: 99%

“…The existing studies do not cover the mobile communication channel model in the actual environment. Experimental and theoretical analysis shows that Rayleigh and Nakagami channel models can not exactly describe the dynamic characteristics of mobile communication channels [25], [26]. The 2-Rayleigh and 2-Nakagami fading models have been considered for mobile communication channels in [27]- [30].…”

Section: Introductionmentioning

confidence: 99%

Physical Layer Security Performance of Wireless Mobile Sensor Networks in Smart City

Wang

Lin

et al. 2019

IEEE Access

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In smart cities, the ubiquitous network connections and high data rate services are provided to afford effective service of real-time monitoring and responses. With the development of the 5G mobile communication technology, the wireless sensor mobile communication networks in the smart city have become a hot issue for academic researches. Due to the openness of wireless channels, the physical layer security of the wireless mobile sensor mobile communication networks in smart city encounters severe challenges. In this paper, based on Wyner's wiretap model, the secrecy performance of the wireless mobile sensor communication networks over 2-Nakagami fading channels is investigated. We derive the exact secure outage probability (SOP) and the probability of strictly positive secrecy capacity expressions for two transmit antenna selection (TAS) schemes. The exact closed-form expressions for the lower bound on the SOP are also derived using the optimal TAS scheme. Then, the system secrecy performance is verified and analyzed by Monte Carlo simulations under different conditions. The simulation results show that the analytical results match perfectly with the Monte Carlo simulation results. Increasing the number of transmit antennas can improve secrecy performance. INDEX TERMS Smart city, wireless mobile sensor networks, physical layer security, secure outage probability, probability of strictly positive secrecy capacity, transmit antenna selection.

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“…Space-time trellis codes (STTC) [1], [2] have garnered significant attention due to their attractive performance gains as a result of the inherent spatio-temporal diversity for multipleinput multiple-output (MIMO) systems [3]. Towards this end, the recent work in [4] employs STTC for vehicular communication while [5] combines STTC systems with space-time shift keying to further improvize the associated performance gains. Further, orthogonal frequency division multiplexing (OFDM) in multi-antenna systems has emerged as one of the key technologies such as 3GPP-LTE, Mobile WiMAX, IMT-Advanced as well as wireless LAN standards like IEEE 802.11a, IEEE 802.11n [6].…”

Section: Introductionmentioning

confidence: 99%

Sparse Bayesian Learning-Aided Joint Sparse Channel Estimation and ML Sequence Detection in Space-Time Trellis Coded MIMO-OFDM Systems

Mishra

Jagannatham

Hanzo

2020

IEEE Trans. Commun.

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Sparse Bayesian learning (SBL)-based approximately sparse channel estimation schemes are conceived for space-time trellis coded (STTC) multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems relying on trellis-based encoding and decoding over the data subcarriers. First, a pilot-aided channel estimation scheme is developed employing the multiple response extension of SBL (MSBL) framework. Subsequently, a novel data-aided joint channel estimation and data decoding framework relying on optimal maximum likelihood sequence detection (MLSD) is intrinsically amalgamated with our powerful EM-based MSBL algorithm. Explicitly, an MSBL-based MIMO channel estimate is gleaned in the E-step followed by a novel modified path-metricbased Viterbi decoder in the M-step. Our theoretical analysis characterizes the performance of the proposed schemes in terms of the associated frame error rate (FER) upper bounds by explicitly considering the effect of estimation errors along with evaluating the product measure of the STTC under consideration. Finally, our simulation results are complemented by the Bayesian Cramér-Rao bound (BCRB), the associated complexity analysis and the performance of the proposed schemes for validating the theoretical bounds.

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STTC design for vehicular communication systems employing fixed‐gain AF PLNC over cascaded fading channels

Cited by 6 publications

References 43 publications

Asymptotic Analysis of MRT Over Double Scattering Channels With MMSE Estimation

Asymptotic Analysis of MRT Over Double Scattering Channels With MMSE Estimation

Physical Layer Security Performance of Wireless Mobile Sensor Networks in Smart City

Sparse Bayesian Learning-Aided Joint Sparse Channel Estimation and ML Sequence Detection in Space-Time Trellis Coded MIMO-OFDM Systems

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