Optimising Resource Efficiency in Future Mobile Communications
Lead Research Organisation:
University of Southampton
Department Name: Electronics and Computer Science
Abstract
Mobile communication systems are becoming more and more complex to design (by researchers), operate (by the operators) and used by the people in the street. Mobile users now wish to be always connected, irrespective of time and place, and have access to a range of new services to help him/her in everyday life, all at the lowest possible cost. Currently no one knows how to evaluate whether a system is efficient or not in such provision. The reason for this is the huge number of parameters involved which collectively influence system efficiency. So far the practice has been to use a subset of such parameters to define localised efficiency -- but this does not provide overall efficiency and it will not lead to low cost or optimum use of scare spectrum. There are three important criteria which need to be considered and designed together to achieve a highly efficient mobile system. These are: quality of offered service, capacity and the cost of the system. Each of these criteria are influenced by a large number of parameters individually, where each have different weightings. Optimum design needs to find a fine balance between the three different criteria and yet currently there is no technique available which enables them to be optimised together to provide the required low cost solution. What makes this difficult is that a mobile system is dynamic by nature in terms of: range of mobility of users, wide range of operational environments, wide range of services with different bit rates and expected qualities, etc. This all points to requirements for a system with a certain degree of adaptability so that the system can self-organise and adapt itself to changing conditions. Currently systems are designed and operated on more or less fixed technique and parameters. These include the design of air-interface, media access control, handover algorithms, cell sizes and fixed frequency band allocation which all lead to wastage of resources and expensive solutions. The mobile systems of the future, addressed herein, are continuously adaptable and reconfigurable and respond automatically to the conditions of environments and user demands. It is only by engaging with these factors that efficiency can be maximised and the required low cost new services can be delivered to users. The challenge of the research described herein is how to collectively design such very complex networks so that users, service providers and network operators will all consider it efficient and cost effective to participate in the mobile vision of the future.
People |
ORCID iD |
Lajos Hanzo (Principal Investigator) |
Publications
Xing C
(2024)
A General Matrix Variable Optimization Framework for MIMO Assisted Wireless Communications
in IEEE Transactions on Vehicular Technology
Winter S
(2024)
A Lattice-Reduction Aided Vector Perturbation Precoder Relying On Quantum Annealing
in IEEE Wireless Communications Letters
Zhu W
(2021)
A New Class of Structured Beamforming for Content-Centric Fog Radio Access Networks
in IEEE Transactions on Communications
Liu M
(2024)
A Nonorthogonal Uplink/Downlink IoT Solution for Next-Generation ISAC Systems
in IEEE Internet of Things Journal
How H
(2006)
A Redundant Residue Number System Coded Burst-by-Burst Adaptive Joint-Detection Based CDMA Speech Transceiver
in IEEE Transactions on Vehicular Technology
Nguyen T
(2008)
A Systematic Luby Transform Coded V-BLAST System
Alamri O
(2007)
A Turbo Detection and Sphere-Packing-Modulation-Aided Space-Time Coding Scheme
in IEEE Transactions on Vehicular Technology
Liu X
(2007)
A Unified Exact BER Performance Analysis of Asynchronous DS-CDMA Systems Using BPSK Modulation over Fading Channels
in IEEE Transactions on Wireless Communications
Gong S
(2021)
A Unified MIMO Optimization Framework Relying on the KKT Conditions
in IEEE Transactions on Communications
Cheng Y
(2023)
Achievable Rate Optimization of the RIS-Aided Near-Field Wideband Uplink
in IEEE Transactions on Wireless Communications
Ni S
(2007)
Adaptive Beamforming and Adaptive Modulation-Assisted Network Performance of Multiuser Detection-Aided FDD and TDD CDMA Systems
in IEEE Transactions on Vehicular Technology
Chen S
(2008)
Adaptive Minimum Symbol Error Rate Beamforming Assisted Detection for Quadrature Amplitude Modulation
in IEEE Transactions on Wireless Communications
Srinivasan M
(2021)
Airplane-Aided Integrated Next-Generation Networking
in IEEE Transactions on Vehicular Technology
Gupta A
(2024)
An Affine Precoded Superimposed Pilot Based mmWave MIMO-OFDM ISAC System
in IEEE Open Journal of the Communications Society
Akhtman J
(2007)
An Optimized-Hierarchy-Aided Approximate Log-MAP Detector for MIMO Systems
in IEEE Transactions on Wireless Communications
SeungHwan Won
(2008)
Analysis of Serial-Search-Based Code Acquisition in the Multiple-Transmit/Multiple-Receive-Antenna-Aided DS-CDMA Downlink
in IEEE Transactions on Vehicular Technology
Liu X
(2007)
Analytical bit error rate performance of DS-CDMA ad hoc networks using large area synchronous spreading sequences
in IET Communications
Garg A
(2024)
Angularly Sparse Channel Estimation in Dual-Wideband Tera-Hertz (THz) Hybrid MIMO Systems Relying on Bayesian Learning
in IEEE Transactions on Communications
Chong Xu
(2008)
Ant-Colony-Based Multiuser Detection for Multifunctional-Antenna-Array-Assisted MC DS-CDMA Systems
in IEEE Transactions on Vehicular Technology
Sui Z
(2021)
Approximate Message Passing Algorithms for Low Complexity OFDM-IM Detection
in IEEE Transactions on Vehicular Technology
Jafri M
(2024)
Asynchronous Distributed Coordinated Hybrid Precoding in Multi-cell mmWave Wireless Networks
in IEEE Open Journal of Vehicular Technology
Srivastava S
(2022)
Bayesian Learning Aided Simultaneous Row and Group Sparse Channel Estimation in Orthogonal Time Frequency Space Modulated MIMO Systems
in IEEE Transactions on Communications
Srivastava S
(2021)
Bayesian Learning Aided Sparse Channel Estimation for Orthogonal Time Frequency Space Modulated Systems
in IEEE Transactions on Vehicular Technology
Rajput K
(2021)
Bayesian Learning-Based Linear Decentralized Sparse Parameter Estimation in MIMO Wireless Sensor Networks Relying on Imperfect CSI
in IEEE Transactions on Communications
Xu S
(2023)
Blockage-Resilient Hybrid Transceiver Optimization for mmWave Communications
in IEEE Transactions on Wireless Communications
Soon Xin Ng
(2006)
Burst-by-burst adaptive decision feedback equalized TCM, TTCM, and BICM for H.263-assisted wireless video telephony
in IEEE Transactions on Circuits and Systems for Video Technology
Bonello N
(2009)
Channel Code-Division Multiple Access and Its Multilevel-Structured LDPC-Based Instantiation
in IEEE Transactions on Vehicular Technology
Akhtman J
(2007)
Channel Impulse Response Tap Prediction for Time-Varying Wireless Channels
in IEEE Transactions on Vehicular Technology
Yang D
(2008)
Closed-loop linear dispersion coded eigen-beam transmission and its capacity
in Electronics Letters
Chen S
(2007)
Clustering-Based Symmetric Radial Basis Function Beamforming
in IEEE Signal Processing Letters
El-Hajjar M
(2007)
Coherent and Differential Downlink Space-Time Steering Aided Generalised Multicarrier DS-CDMA
in IEEE Transactions on Wireless Communications
Tan S
(2023)
Communication-Assisted Multi-Agent Reinforcement Learning Improves Task-Offloading in UAV-Aided Edge-Computing Networks
in IEEE Wireless Communications Letters
Liu K
(2022)
Compact User-Specific Reconfigurable Intelligent Surfaces for Uplink Transmission
in IEEE Transactions on Communications
Akhtman J
(2009)
Constrained Capacity of Delay-Limited Wireless Transceivers
Bonello N
(2008)
Construction of Regular Quasi-Cyclic Protograph LDPC Codes Based on Vandermonde Matrices
in IEEE Transactions on Vehicular Technology
Shen L
(2024)
D-STAR: Dual Simultaneously Transmitting and Reflecting Reconfigurable Intelligent Surfaces for Joint Uplink/Downlink Transmission
in IEEE Transactions on Communications
R Zhang
(2009)
Decentralised High-Throughput Non-Orthogonal Interleaved Random Space-Time Coding for Multi-Source Cooperation
in IEEE Transactions on Vehicular Technology
Akhtman J
(2007)
Decision Directed Channel Estimation Aided OFDM Employing Sample-Spaced and Fractionally-Spaced CIR Estimators
in IEEE Transactions on Wireless Communications
Kumar P
(2023)
Decision Fusion in Centralized and Distributed Multiuser Millimeter Wave Massive MIMO-OFDM Sensor Networks
in IEEE Open Journal of the Communications Society
Chen J
(2023)
Deep Learning Aided LLR Correction Improves the Performance of Iterative MIMO Receivers
in IEEE Transactions on Vehicular Technology
Hoang T
(2022)
Deep Learning Aided Physical-Layer Security: The Security Versus Reliability Trade-Off
in IEEE Transactions on Cognitive Communications and Networking
Van Luong T
(2022)
Deep Learning-Aided Optical IM/DD OFDM Approaches the Throughput of RF-OFDM
in IEEE Journal on Selected Areas in Communications
He D
(2021)
Deep Learning-Assisted TeraHertz QPSK Detection Relying on Single-Bit Quantization
in IEEE Transactions on Communications
Liu D
(2022)
Deep-Learning-Aided Packet Routing in Aeronautical Ad Hoc Networks Relying on Real Flight Data: From Single-Objective to Near-Pareto Multiobjective Optimization
in IEEE Internet of Things Journal
Won S
(2007)
Differentially coherent code acquisition in the MIMO-aided multi-carrier DS-CDMA downlink
in IET Communications
Chandra D
(2022)
Direct Quantum Communications in the Presence of Realistic Noisy Entanglement
in IEEE Transactions on Communications
Chawla A
(2021)
Distributed Detection for Centralized and Decentralized Millimeter Wave Massive MIMO Sensor Networks
in IEEE Transactions on Vehicular Technology
El-Hajjar M
(2009)
Distributed Turbo Coding in the Presence of Inter-User Channel Impairment
Description | Numerous sophisticated transmission and reception schemes were conceived, including multi-user detectors, Interleave Division Multiple Access (IDMA) schemes, Multi-user transmitters, sphere-decoders, etc; |
Exploitation Route | They have been exploited by the 20 or so companies of the Mobile Virtual Centre of Excellence (MVCE) and by the academic community through our publications and books; |
Sectors | Aerospace, Defence and Marine,Creative Economy,Education,Electronics,Healthcare,Transport |
URL | httP://www-mobile.ecs.soton.ac.uk |
Description | The companies of the MVCE created mobile phone products; |
First Year Of Impact | 2006 |
Sector | Aerospace, Defence and Marine,Creative Economy,Digital/Communication/Information Technologies (including Software),Education,Electronics,Transport |
Impact Types | Cultural,Societal,Economic |
Description | European Union Framework 7 |
Amount | £240,000 (GBP) |
Funding ID | Concerto propject |
Organisation | European Commission |
Department | Seventh Framework Programme (FP7) |
Sector | Public |
Country | European Union (EU) |
Start | 02/2012 |
End | 12/2014 |
Description | VCE Mobile & Personal Comm Ltd |
Organisation | VCE Mobile & Personal Comm Ltd |
Country | United Kingdom |
Sector | Private |
Start Year | 2006 |