User Tools

Site Tools


specees

Differences

This shows you the differences between two versions of the page.

Link to this comparison view

Next revision
Previous revision
specees [2019/08/03 08:51]
lingjialiu created
specees [2019/08/03 09:45] (current)
lingjialiu
Line 6: Line 6:
  
 \\ \\
-<WRAP centeralign><​fs large>**Spatial ​Spectrum ​Sensing-Based Device-to-Device (D2D) Networks**</​fs>​\\+<WRAP centeralign><​fs large>​** ​NSF/​ECCS-1811497:​ Enabling ​Spectrum ​and Energy-Efficient Dynamic Spectrum Access Wireless ​Networks ​using Neuromorphic Computing**</​fs>​\\
 \\ \\
 </​WRAP>​ </​WRAP>​
Line 14: Line 14:
 ==== Personnel ==== ==== Personnel ====
  
-  * Principal Investigator:​ Lingjia Liu (ECE at VT) +  * Principal Investigator ​in the Leading Institution: Lingjia Liu (ECE at VT) 
-  * Student ​Investigator: ​Bodong Shang (ECE at VT) +  * Co-Principal ​Investigator ​in the Leading Institution[[https://​www.yangyi.ece.vt.edu/​index.html|Yang Yi]] (ECE at VT) 
-  * Student ​Investigator: ​Jianan Bai (ECE at VT+  * Principal ​Investigator ​in the Collaborative Institution[[https://​www.ele.uri.edu/​faculty/​he/​|Haibo He]] (ECBE at URI
-  * Industrial CollaboratorJianzhong ​(Charlie) Zhang (Samsung Research America+  * Student InvestigatorHao-Hsuan Chang (ECE at VT
-  * Industrial CollaboratorHao Chen (Samsung Research America+  * Student InvestigatorKian Hamedani ​(ECE at VT
-  * Academic CollaboratorHarpreet S. Dhillon ​(ECE at VT)+  * Student InvestigatorHe Jiang (ECBE at URI)
  
 ==== Abstract ==== ==== Abstract ====
  
-<WRAP justify> ​The continuing growth ​of mobile ​data applications is expected to trigger a large increase in mobile traffic over the next decade. ​Direct device-to-device (D2D) communications between user devices ​that offload cellular network traffic ​has a great potential ​to be an integral part of the solution to address this mobile ​data challengeIn this project, ​the researchers will introduce a novel spectrum access modelcalled sensing-based D2D communication,​ to significantly improve the overall network spectral-efficiency ​of a mobile broadband network. In sensing-based D2D, users utilize spatial spectrum sensing ​to explore ​temporal and spatial ​spectrum ​transmission ​opportunities ​within the underlying cellular network bandsEquipped with spatial spectrum sensingthese users can efficiently utilize the available non-occupied cellular ​spectrum ​while providing enough protection ​to legacy base-station-to-device usersThis project ​will result ​in new enabling technology ​for future mobile broadband ​networks and will also effectively enrich educational materials by providing software ​and hardware-based implementation ​and experimental activities.+<WRAP justify> ​During the last two decades, the use of Radio Frequency (RF) spectrum has increased tremendously due to the ever growing demand for wireless connectivity. The existing network technologies that support the current wireless ​data demand are expected to increase ​their capacity significantly ​in the next decade, calling for spectrum and energy efficient communication strategiesThere are two popular approaches ​to efficiently utilize the RF spectrum: One is the cognitive radio networks which allow mobile users to share the spectrum ​that has been primarily allocated ​to other services such as television broadcasting,​ global position system (GPS), radar, weather forecasting,​ etc., provided that the mobile ​users impose limited interference to existing servicesAnother approach is to enhance ​the mobile broadband networks via expanded bandwidthmassive Multiple-Input Multiple-Output (MIMO) systems, and densified heterogeneous networks (HetNets). However, both approaches have limitations and have different impacts on spectrum efficiency and energy ​efficiency. In additioncurrent hardware platforms exhibit formidable challenges in supporting high computational complexity and low power consumption. This project introduces a novel network architecture and its application-specific hardware optimization using neuromorphic computing devices. The new wireless network architecture allows mobile ​users to perform spatio-temporal ​spectrum sensing ​and actively search for dynamic ​spectrum ​access (DSA) opportunities ​to enable short-range and local communicationsMeanwhileneuromorphic computing devices that mimic bio-neurological processes will be designed to tackle the high computational complexity of the new dynamic ​spectrum ​access approach with extremely low power consumption. In this way, we will be able to enable our nation'​s next-generation wireless communications and networking that are intelligent,​ spectrum-efficient, and energy-efficient in a dynamic spectrum environmentThe developed concepts and technologies ​will also help achieve National Broadband Plan which targets at significant improvements ​in the efficiency of RF spectrum utilization. The project has an extensive education and outreach plan which includes designing ​new course components on energy-efficient communications,​ analog neuron circuits, and computational intelligence ​for wireless ​networks, joint training of graduate ​and undergraduate researchers between the two collaborative institutions, ​and outreach to telecommunication industry and underrepresented students through seminars ​and diversity programs.
  
-{{ :​cluster_d2d.jpg?400 |}} +Short-range and local communications are extremely beneficial for spectrum and energy efficiency. The research ​objective of the project is to 1) design ​DSA-enabled HetNets to enable short-range/​local ​spectrum ​access ​to improve ​the spectrum and energy efficiency, and 2) leverage neuromorphic computing architecture to efficiently solve the associated ​resource allocation ​problems with extremely high energy efficiencyTo achieve the goalthe project is organized ​into four interconnected research thrusts. Thrust 1 focuses on spatio-temporal spectrum ​sensing ​with MIMO transceivers. Thrust 2 investigates cooperative communications and resource allocation for DSA-enabled HetNets. Thrust 3 studies neuromorphic computing ​based hardware design for DSA-enabled HetNetsThrust 4 develops ​and evaluates the hardware-software ​test-bed. The proposed ​paradigm shift from centralized base-station-controlled approach to the decentralized approach will revolutionize ​the future wireless network design, where the individual users will play stronger role in spectrum access and drastically change the network topology by utilizing neuromorphic computing devices. The hardware-software co-design methodologies ​developed in this project ​can be readily applied ​to other related fields: computer communication networks, cyber security, and energy-harvesting communications,​ etc.
- +
-The research ​project has three interconnected thrusts. In the first thrust, a comprehensive framework for both theoretical analysis and practical ​design ​of sensing-based D2D that connects the user-driven spatial ​spectrum ​sensing ​to the overall network performance will be developedusing detection theory ​and stochastic geometry. In the second thrust, optimal system design and resource allocation ​of sensing-based D2D will be identifiedExisting techniques, such as distributed caching and millimeter wave communicationswill be integrated ​into sensing-based ​D2DIn the third thrust, the performance of the developed schemes will be evaluated using both software ​and hardware test-beds to obtain ideas on real-world performance. The key aspect of the proposed ​research is that the success of the project ​will lead to a big shift from currently popular ​design methodologies ​used for wireless networks and can provide a comprehensive response ​to mobile data growth challenge under realistic system assumptions.+
 </​WRAP>​ </​WRAP>​
  
Line 33: Line 31:
  
 <WRAP justify> ​ <WRAP justify> ​
 +
 +  * H. Song, L. Liu, S. Pudlewski, and E. Bentley, "​Random Network Coding Enabled Routing in Swarm Unmanned Aerial Vehicle Networks",​ accepted to 2019 //IEEE Global Commun. Conf.// (GLOBECOM).
 +
 +  * B. Shang, L. Liu, J. Ma, and P. Fan, "​Unmanned Aerial Vehicle (UAV) Meets Vehicle-to-Everything in Secure Communications",​ accepted to //IEEE Commun. Mag.//​. ​
  
   * A. Akhtar, J. Ma, R. Shafin, J. Bai, L. Li, Z. Li, and L. Liu, "Low Latency Scalable Point Cloud Communication in VANETs using V2I Communication",​ accepted to 2019 //IEEE Intl Conf. on Commun.// (ICC).   * A. Akhtar, J. Ma, R. Shafin, J. Bai, L. Li, Z. Li, and L. Liu, "Low Latency Scalable Point Cloud Communication in VANETs using V2I Communication",​ accepted to 2019 //IEEE Intl Conf. on Commun.// (ICC).
Line 39: Line 41:
  
   * F. Mahmood, E. Perrins and L. Liu, "​Energy-Efficient Wireless Communications:​ From Energy Modeling to Performance Evaluation,"​ accepted to //IEEE Trans. Veh. Technol.//, 2019.   * F. Mahmood, E. Perrins and L. Liu, "​Energy-Efficient Wireless Communications:​ From Energy Modeling to Performance Evaluation,"​ accepted to //IEEE Trans. Veh. Technol.//, 2019.
- 
-  * H. Chen, L. Liu, H. S. Dhillon and Y. Yi, "​QoS-Aware D2D Cellular Networks with Spatial Spectrum Sensing: A Stochastic Geometry View," //IEEE Trans. on Commun.//, vol. 67, no. 5, pp. 3651-3664, May 2019. 
  
   * C. Sahin, L. Liu, E. Perrins, and L. Ma, "​Delay-Sensitive Communications over IR-HARQ: Modulation, Coding Latency, and Reliability",​ Special Issue on Ultra-Reliable Low-Latency Communications in Wireless Networks, //IEEE J. Sel. Area Commun.//, vol. 37, no. 4, pp. 749 - 764, April 2019.   * C. Sahin, L. Liu, E. Perrins, and L. Ma, "​Delay-Sensitive Communications over IR-HARQ: Modulation, Coding Latency, and Reliability",​ Special Issue on Ultra-Reliable Low-Latency Communications in Wireless Networks, //IEEE J. Sel. Area Commun.//, vol. 37, no. 4, pp. 749 - 764, April 2019.
 +
 +  * First release of our code on Brain-Inspired Computing Meets MIMO-OFDM can be found [[https://​github.com/​JohnJohnZhou/​ESN_MIMO_v1|here]].\\
 +
 +  * H. Jiang, H. He, L. Liu and Y. Yi, "​Q-Learning for Non-Cooperative Channel Access Game of Cognitive Radio Networks,"​ 2018 //Intl Joint Conf. on Neural Netw.// (IJCNN), Rio de Janeiro, 2018, pp. 1-7.
  
   * R. Atat, L. Liu, J. Wu, G. Li, C. Ye and Y. Yang, "Big Data Meet Cyber-Physical Systems: A Panoramic Survey,"​ //IEEE Access//, vol. 6, pp. 73603-73636,​ 2018.   * R. Atat, L. Liu, J. Wu, G. Li, C. Ye and Y. Yang, "Big Data Meet Cyber-Physical Systems: A Panoramic Survey,"​ //IEEE Access//, vol. 6, pp. 73603-73636,​ 2018.
specees.1564836716.txt.gz · Last modified: 2019/08/03 08:51 by lingjialiu