Performances of Transmit Antenna Selection, Receive Antenna Selection, and Maximal-Ratio-Combining-Based Hybrid Techniques in the Presence of Feedback Errors

Yılmaz, Ahmet; Kucur, Oğuz

doi:10.1109/tvt.2013.2267962

Cited by 26 publications

(8 citation statements)

References 19 publications

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“…Performance of the proposed TAS schemes is analysed in the previous section assuming the PF. However, in real-world wireless communications, the TAS schemes face various practical impairments such as channel estimation error, feedback delay (FD) and FE [16,[34][35][36][37][38]. In this section, the error performance of the proposed schemes is analysed in the presence of FE, assuming the perfect channel estimation and no FD.…”

Section: Performance Analysis With Fementioning

confidence: 99%

Performance analysis of differential chaos shift keying modulation with transmit antenna selection

Kumar¹,

Sahu²

2016

IET Communications

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Section: Performance Analysis With Fementioning

confidence: 99%

Performance analysis of differential chaos shift keying modulation with transmit antenna selection

Kumar¹,

Sahu²

2016

IET Communications

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“…To obtain the outage performance and average SER of the interested CC-MIMO multiuser downlink transmission systems, (10) indicates that the statistical descriptions of the RVs γ 1 , γ 2 , and γ 3 are required firstly [30][31][32][33]. Therefore, in this section, we first present the statistical descriptions for the RVs γ 1 , γ 2 , and γ 3 as well as the detailed proof, which will be frequently utilized in the sequent derivations.…”

Section: Outdate Csimentioning

confidence: 99%

Performance analysis of cooperative cognitive MIMO multiuser downlink transmission with perfect and imperfect CSI over Rayleigh fading channels

Jia

Wang

Dang

et al. 2015

J Wireless Com Network

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In this paper, a comprehensive comparison analysis in terms of outage probability and average symbol error ratio (SER) is presented for cooperative cognitive multiple-input and multiple-output (CC-MIMO) multiuser systems with amplify-and-forward (AF) protocol. Specially, we consider two scenarios where the CC-MIMO multiuser systems have the perfect and imperfect channel state information (CSI). The CC-MIMO multiuser systems consist of one multi-antenna source, one single-antenna relay, and multiple multi-antenna destinations. At the secondary source and destinations, the maximal ratio transmission (MRT) and maximal ratio combining (MRC) are employed, respectively. For such CC-MIMO multiuser systems, we first obtain the exact closed-form expressions of outage probability under the two cases where the CC-MIMO multiuser systems have the perfect and imperfect CSI. Then, to reduce the implementation complexity, the tight lower bounds of outage probability and average SER are derived. Finally, to obtain insight, by using the high signal-to-noise ratio (SNR) approximation, the asymptotic estimations of outage probability are achieved. The numerical results show that the derivations are agreed with the simulations, which validate our derivations. At the same time, the results show that, for the systems without perfect CSI, the achievable diversity order reduces to one, regardless of the number of antennas at the cognitive source and destinations as well as the number of the cognitive destinations. Nevertheless, these key parameters affect the coding gain of the CC-MIMO multiuser systems. When the systems have the perfect CSI (or without feedback delay), the achievable diversity gain is determined by the minimum between the number of source's antennas and the product of the number of destinations and the number of destination's antennas. For the effect of PU's parameters, our results indicate that primary systems only affect the coding gain but not the diversity gain.

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“…The transmit power and the number of active antennas are jointly optimized to get the highest energy efficiency [27]. The performance of actual antenna systems using the antenna selection methods is evaluated and examined in [28,29,30].…”

Section: Introductionmentioning

confidence: 99%

Array resource allocation for radar and communication integration network

2020

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A radar and communication integration (RCI) system has great flexibility in allocating antenna resources to guarantee both radar and communication performance. This paper considers the array allocation problems for multiple target localization and multiple platforms communication in an RCI network. The objective of array allocation is to maximize the communication capacity for each channel and to minimize the localization error for each target. In this paper, we firstly build a localization and communication model for array allocation in an RCI network. Minorization maximization (MM) is then applied to create surrogate functions for multiple objective optimization problems. The projected gradient descent (PGD) method is further employed to solve two array allocation problems with and without a certain communication capacity constraint. Computer simulations are conducted to evaluate the performance of the proposed algorithms. The results show that the proposed algorithms have improved localization and communication performance after efficiently allocating the array

show abstract

Performances of Transmit Antenna Selection, Receive Antenna Selection, and Maximal-Ratio-Combining-Based Hybrid Techniques in the Presence of Feedback Errors

Cited by 26 publications

References 19 publications

Performance analysis of differential chaos shift keying modulation with transmit antenna selection

Performance analysis of differential chaos shift keying modulation with transmit antenna selection

Performance analysis of cooperative cognitive MIMO multiuser downlink transmission with perfect and imperfect CSI over Rayleigh fading channels

Array resource allocation for radar and communication integration network

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