Feedback Strategies for Multicell Systems

Özbek, Berna; Ruyet, Didier Le

doi:10.1007/978-1-4614-7741-9_7

Cited by 4 publications

(9 citation statements)

References 52 publications

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“…However, Alice has no knowledge about CSI of Eve, which is a highly probable scenario in practical cases since Eve is passive in general. We consider a clustering structure where adjacent subcarriers are grouped and only one representative value for each cluster is selected [7].…”

Section: System Modelmentioning

confidence: 99%

“…We then apply a rotation for each codeword to obtain the rotated codebook for each generated orthogonal vectors by

{bold-italicC}_{j, n, m, q}^{normalrot} = {bold-italicU}_{n, m, q}^{normalrot} {bold-italicC}_{j}^{ϵ}; j = 1, \dots, 2^{B} .

Then, the rotated codebook for each rotation vector is constructed by

C_{n, m, q}^{normalrot} = false[{bold-italicC}_{1, n, m, q}^{normalrot}, \dots, {bold-italicC}_{2^{B}, n, m, q}^{normalrot} false]

. With a specific codebook design, the quantisation error is reduced since only the local region is quantised instead of the whole region [7]. Step 4: By using the rotated codebook designed in step 3 , the CDI of each cluster in the set of

Q_{n, m}

obtained step 2 is quantised according to the following rule:

j_{n, m, q}^{normalrot} = \underset{1 \leq j \leq 2^{B}}{\arg truemin} d_{c}^{2} false({bold-italicG}_{q}, {bold-italicC}_{j, n, m, q}^{normalrot} false) .

Then, the corresponding indexes of the quantised CSI,

j_{n, m, q}^{normalrot}; normal∀ n, m, q

, are fed back to the Alice through the limited feedback link.…”

Section: Proposed Spatial Signature For Secure Communicationsmentioning

confidence: 99%

“…We then apply a rotation for each codeword to obtain the rotated codebook for each generated orthogonal vectors by

{bold-italicC}_{j, n, m, q}^{normalrot} = {bold-italicU}_{n, m, q}^{normalrot} {bold-italicC}_{j}^{ϵ}; j = 1, \dots, 2^{B} .

Then, the rotated codebook for each rotation vector is constructed by

C_{n, m, q}^{normalrot} = false[{bold-italicC}_{1, n, m, q}^{normalrot}, \dots, {bold-italicC}_{2^{B}, n, m, q}^{normalrot} false]

. With a specific codebook design, the quantisation error is reduced since only the local region is quantised instead of the whole region [7].…”

Section: Proposed Spatial Signature For Secure Communicationsmentioning

confidence: 99%

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Spatial signature for secure MISO‐OFDM systems

Özbek

Kurt

2018

Electron. lett.

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Physical layer security is a promising approach to establish secure communications based on the characteristics of wireless channels. A spatial signature based secure multiple-input single-output (MISO) orthogonal frequency division multiplexing (OFDM) system is proposed to disrupt the reception of a passive eavesdropper by holding two practically relevant assumptions: a limited feedback link for legitimate node and the unavailability of channel state information of eavesdropper. The proposed algorithm achieves a higher average secrecy rate than the conventional secure MISO-OFDM systems in presence of a limited feedback link.

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Section: System Modelmentioning

confidence: 99%

“…We then apply a rotation for each codeword to obtain the rotated codebook for each generated orthogonal vectors by

{bold-italicC}_{j, n, m, q}^{normalrot} = {bold-italicU}_{n, m, q}^{normalrot} {bold-italicC}_{j}^{ϵ}; j = 1, \dots, 2^{B} .

Then, the rotated codebook for each rotation vector is constructed by

C_{n, m, q}^{normalrot} = false[{bold-italicC}_{1, n, m, q}^{normalrot}, \dots, {bold-italicC}_{2^{B}, n, m, q}^{normalrot} false]

Q_{n, m}

obtained step 2 is quantised according to the following rule:

j_{n, m, q}^{normalrot} = \underset{1 \leq j \leq 2^{B}}{\arg truemin} d_{c}^{2} false({bold-italicG}_{q}, {bold-italicC}_{j, n, m, q}^{normalrot} false) .

Then, the corresponding indexes of the quantised CSI,

j_{n, m, q}^{normalrot}; normal∀ n, m, q

, are fed back to the Alice through the limited feedback link.…”

Section: Proposed Spatial Signature For Secure Communicationsmentioning

confidence: 99%

“…We then apply a rotation for each codeword to obtain the rotated codebook for each generated orthogonal vectors by

{bold-italicC}_{j, n, m, q}^{normalrot} = {bold-italicU}_{n, m, q}^{normalrot} {bold-italicC}_{j}^{ϵ}; j = 1, \dots, 2^{B} .

Then, the rotated codebook for each rotation vector is constructed by

C_{n, m, q}^{normalrot} = false[{bold-italicC}_{1, n, m, q}^{normalrot}, \dots, {bold-italicC}_{2^{B}, n, m, q}^{normalrot} false]

. With a specific codebook design, the quantisation error is reduced since only the local region is quantised instead of the whole region [7].…”

Section: Proposed Spatial Signature For Secure Communicationsmentioning

confidence: 99%

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Spatial signature for secure MISO‐OFDM systems

Özbek

Kurt

2018

Electron. lett.

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“…The eNBs of each of these clusters exchange information with one another and jointly process signals. Furthermore, multiple User Equipments (UEs) can receive their signals simultaneously from one or more transmission points in a coordinated or jointprocessing manner [12,18]. In [19] authors study the performance analysis of the CoMP joint processing (JP) transmission in HetNets scenarios.…”

Section: Background and Related Workmentioning

confidence: 99%

Handover enhancement for LTE-Advanced and beyond heterogeneous cellular networks

Kazi

Wainer

2017

2017 International Symposium on Performance Evaluation of Computer and Telecommunication Systems (SPECTS)

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Heterogeneous networks (HetNets) are considered a promising cellular network architecture to provide services to the massive number of subscribers. However, in heterogeneous networks, as cell size becomes smaller, the number of handovers and handover failure increase significantly. Therefore, mobility management becomes an important issue in HetNets. In this research, we analyzed the handover parameters, and proposed a novel handover method for heterogeneous cellular networks to minimize the number of handovers and handover failure. In the proposed method, we considered dual connectivity with control and data plane split and Coordinated Multipoint (CoMP) transmission to optimize the handover parameters. The reduction of handover improves the network performance and the handover failure reduction improves the user experience. The simulation results show that the proposed handover process significantly reduces the number of handovers in heterogeneous cellular networks.

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“…The eNBs of each of the cooperation set exchange information among them, and they process signals and provide services to the users jointly. As a result, the UEs can receive their signals simultaneously from one or more transmission points in a coordinated or joint-processing method, which can improve data rate coverage and cell edge throughput [14,15]. Though the idea of CoMP was introduced in LTE-Advanced networks, it is also considered as a key feature for future dense cellular networks to improve the spectral efficiency, throughput and cell edge performance [16,11].…”

Section: Motivationmentioning

confidence: 99%

Dynamic Coordination Architecture and Mobility Management for Next Generation Cooperative Cellular Networks

Kazi¹

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The fundamental challenges of existing cellular wireless networks are the exponential demand of mobile data traffic, higher data rates, massive numbers of user-coverage and lower latency. Moreover, the next generation of wireless cellular networks also consider potential use cases, such as autonomous vehicle control, smart cities, remote surgery and eHealth, tactile internet, etc. To address these challenges and potential use cases, network densification such as ultra-dense heterogeneous networks (UDHetNet) and multi-cell cooperation are considered as the foundation to support the 1000× capacity challenge in the next generation wireless cellular networks.In this thesis, we study the coordination architecture and mobility management of multicell cooperative communications and present novel algorithms to improve the performance of multi-cell cooperative cellular networks. We propose DCEC: Direct CSI-feedback to Elected Coordination-station, a CoMP coordination architecture for cooperative communication to improve the performance of cellular networks, reducing the signaling overhead and latency. We extended the DCEC approach to heterogeneous cellular networks named DCEC-HetNet as well. We also propose a handover procedure for heterogeneous multi-cell cooperative cellular networks named EHoLM: Enhanced Handover for Low and Moderate speed UEs. The goal of the EHoLM handover procedure is to improve the system performance and user experience, reducing the number of handovers, handover oscillation and handover failure rate. To examine the performance of the proposed algorithms we use the discrete event system specifications (DEVS) for modeling and simulation of cellular networks employing the DCEC and EHoLM methods.

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Feedback Strategies for Multicell Systems

Cited by 4 publications

References 52 publications

Spatial signature for secure MISO‐OFDM systems

Spatial signature for secure MISO‐OFDM systems

Handover enhancement for LTE-Advanced and beyond heterogeneous cellular networks

Dynamic Coordination Architecture and Mobility Management for Next Generation Cooperative Cellular Networks

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