ITU Journal Volume 2 (2021), Issue 6 - Wireless communication systems in beyond 5G era
Editorial Board
Table of Contents
List of Abstracts
WHY DO WE NEED 6G?
     1. INTRODUCTION
     2. THE COMMUNICATION PANORAMABEFORE 5G
          2.1 The standardization and architecture ofwireless cellular networks
          2.2 The dawn of cloud computing and thestandardization of softwarized networks
     3. THE ADVENT AND THE EVOLUTION OF5G
          3.1 Performance and metrics
          3.2 5G architectural characteristics
     4. THE CONCEPT AND VISIONS OF 6G
          4.1 Envisioned performance and metrics
          4.2 Targeted architectural characteristics
     5. WHAT SHOULD 6G BE?
          5.1 Performance indicators and metrics
          5.2 Network virtualisation and campus networksin 6G
          5.3 The tactile internet and digital twins
          5.4 The uni����ication of terrestrial, aerial, andsatellite networks
          5.5 The role of intelligence in 6G
          5.6 Beyond Shannon with semantic communications
          5.7 Quantum and molecular communications
     6. CONCLUSION
     ACKNOWLEDGEMENT
     ACRONYMS
     REFERENCES
     AUTHORS
DEEP EXTENDED FEEDBACK CODES
     1. INTRODUCTION
     2. DEFINITION OF DEEP EXTENDED FEEDBACKCODE
          2.1 QAM/PAM modulator
          2.2 Extended feedback
          2.3 Parity Symbol Generator (PSG)
          2.4 Mitigation of unequal bit errordistribution
          2.5 DEF decoder
     3. TRANSCEIVER TRAINING
     4. PERFORMANCE EVALUATIONS
     5. CONCLUSION AND FURTHER WORK
     REFERENCES
     AUTHORS
MMWAVE MASSIVE ANALOG RELAY MIMO
     1. INTRODUCTION
     2. Mmwave massive analog relay MIMO
          2.1 System model of massive analog relay
          2.2 Artificial channel response by massive analog relay
          2.3 Artificial MIMO channel matrix
          2.4 Noise vector with massive analog relay
          2.5 MIMO channel capacity with beam selection
          2.6 Sequential quasi-optimization procedure
     3. expansion to multi-hop
          3.1 Extension of artificial channel response with multi-hop massive analog relay
          3.2 Noise vector with multi-hop analog relay
          3.3 Beam selection algorithm based on routing
     4. numerical analySis
          4.1 Simulation environment
               4.1.1 Simulation model
               4.1.2 Antenna characteristics
               (a) BS antenna
               (b)  UE antenna
               (c) RS antenna
          4.2 Results of numerical analysis
               4.2.1 One-dimensional arrangement model
               4.2.2 Two-dimensional arrangement model
               1) LOS environment
               2) NLOS environment
               3) Grid environment
          4.3 Discussions
     5. Conclusion
     REFERENCES
     AUTHORS
MULTI‑TIER MULTI‑TENANT NETWORK SLICING: A MULTI‑DOMAIN GAMES APPROACH
     1. INTRODUCTION
          1.1 Contributions
          1.2 Article organisation
     2. RELATED WORK
     3. SYSTEM MODEL
          3.1 Network players
          3.2 Physical network
          3.3 Slice‑user categorisation
          3.4 V2X communication model
          3.5 Channel model
     4. MULTI‑DOMAINGAMES FRAMEWORK
     5. RESOURCE ALLOCATION FRAMEWORK
          5.1 Service Provider‑slice user layer
          5.2 Latency and delay model
          5.3 Resource allocation model
     6. PROBLEM FORMULATION
     7. PROPOSED SOLUTIONS
          7.1 Slice user multi‑tier multi‑domain associationproblem
          7.2 SP‑MVNO resource allocation
          7.3 Monte Carlo method
     8. COMPLEXITY ANALYSIS
          8.1 Computational complexity of the multitiermulti‑domain slice user association
          8.2 Computational complexity of the distributedrecursive backtracking multiplayermulti‑domain
          8.3 Computational complexity of the multitiermulti‑tenant multi‑slice multi‑domainresource allocation
     9. NUMERICAL RESULTS
MASSIVE DISTRIBUTED IRS AIDED WIRELESS COMMUNICATION WITH ON/OFF SELECTION
     1. Introduction
     2. Massive Distributed IRS Aided Wireless Communication with ON/OFF Selection
          2.1 System model
          2.2 Formulation of optimization problem
     3. IRS Reflector Clustering
          3.1 Random method
          3.2 k-means method
          3.3 Proposed method
     4. Simulation evaluation
          4.1 Comparison of channel capacities
          4.2 Number of clusters and performance
     5. Experimental Evaluation
     6. Conclusion
     REFERENCES
     AUTHORS
INDEX OF AUTHORS