Cellular communications systems in congested environments : resource allocation and end-to-end quality of service solutions with MATLAB /
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| Author / Creator: | Ghorbanzadeh, Mo, author. |
|---|---|
| Imprint: | Switzerland : Springer International Publishing, [2017] ©2017 |
| Description: | 1 online resource (xvii, 247 pages) |
| Language: | English |
| Subject: | |
| Format: | E-Resource Book |
| URL for this record: | http://pi.lib.uchicago.edu/1001/cat/bib/11267715 |
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| 100 | 1 | |a Ghorbanzadeh, Mo, |e author. | |
| 245 | 1 | 0 | |a Cellular communications systems in congested environments : |b resource allocation and end-to-end quality of service solutions with MATLAB / |c Mo Ghorbanzadeh, Ahmed Abdelhadi, Charles Clancy. |
| 264 | 1 | |a Switzerland : |b Springer International Publishing, |c [2017] | |
| 264 | 4 | |c ©2017 | |
| 300 | |a 1 online resource (xvii, 247 pages) | ||
| 336 | |a text |b txt |2 rdacontent | ||
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| 504 | |a Includes bibliographical references and index. | ||
| 588 | 0 | |a Print version record. | |
| 505 | 0 | |6 880-01 |a Quality of Service in Communication Systems -- Utility Functions and Radio Resource Allocation -- Centralized Resource Allocation -- Distributed Resource Allocation -- Resource Allocation Architectures Traffic and Sensitivity Analysis -- Radio Resource Block Allocation -- Spectrum-Shared Resource Allocation -- Delay-Based Backhaul Modeling -- Book Summary. | |
| 520 | |a This book presents a mathematical treatment of the radio resource allocation of modern cellular communications systems in contested environments. It focuses on fulfilling the quality of service requirements of the living applications on the user devices, which leverage the cellular system, and with attention to elevating the users? quality of experience. The authors also address the congestion of the spectrum by allowing sharing with the band incumbents while providing with a quality-of-service-minded resource allocation in the network. The content is of particular interest to telecommunications scheduler experts in industry, communications applications academia, and graduate students whose paramount research deals with resource allocation and quality of service. | ||
| 630 | 0 | 0 | |a MATLAB. |0 http://id.loc.gov/authorities/names/n92036881 |
| 630 | 0 | 7 | |a MATLAB. |2 fast |0 (OCoLC)fst01365096 |
| 650 | 0 | |a Wireless communication systems. |0 http://id.loc.gov/authorities/subjects/sh92006740 | |
| 650 | 0 | |a Cell phone systems. |0 http://id.loc.gov/authorities/subjects/sh98004793 | |
| 650 | 0 | |a Quality of service (Computer networks) |0 http://id.loc.gov/authorities/subjects/sh2012001112 | |
| 650 | 7 | |a TECHNOLOGY & ENGINEERING |x Mechanical. |2 bisacsh | |
| 650 | 7 | |a Cell phone systems. |2 fast |0 (OCoLC)fst01734555 | |
| 650 | 7 | |a Quality of service (Computer networks) |2 fast |0 (OCoLC)fst01895136 | |
| 650 | 7 | |a Wireless communication systems. |2 fast |0 (OCoLC)fst01176209 | |
| 650 | 7 | |a Imaging systems & technology. |2 bicssc | |
| 650 | 7 | |a Information retrieval. |2 bicssc | |
| 650 | 7 | |a Optimization. |2 bicssc | |
| 650 | 7 | |a Computer networking & communications. |2 bicssc | |
| 650 | 7 | |a Communications engineering |x telecommunications. |2 bicssc | |
| 650 | 1 | 4 | |a Engineering. |
| 650 | 2 | 4 | |a Communications Engineering, Networks. |
| 650 | 2 | 4 | |a Signal, Image and Speech Processing. |
| 650 | 2 | 4 | |a Information Storage and Retrieval. |
| 650 | 2 | 4 | |a Continuous Optimization. |
| 650 | 2 | 4 | |a Input/Output and Data Communications. |
| 655 | 4 | |a Electronic books. | |
| 700 | 1 | |a Abdelhadi, Ahmed, |e author. | |
| 700 | 1 | |a Clancy, Charles, |e author. | |
| 776 | 0 | 8 | |i Print version: |t Cellular Communications Systems in Congested Environments. |d [Place of publication not identified] : Springer Verlag 2016 |z 9783319462653 |w (OCoLC)957140701 |
| 880 | 0 | 0 | |6 505-01/(S |g Machine generated contents note: |g 1. |t Quality of Service in Communication Systems -- |g 1.1. |t Current Trends in End-to-End QoS in Cellular Networks -- |g 1.1.1. |t QoS in Wireless Networks -- |g 1.1.2. |t QoS in Wired IP Networks -- |g 1.2. |t Congested and Contested Spectrum -- |g 1.3. |t Network Quality of Service Challenges -- |g 1.4. |t Problem Statement -- |g 1.5. |t Book High Level Overview -- |g 1.6. |t Chapters Organization -- |t References -- |g 2. |t Utility Functions and Radio Resource Allocation -- |g 2.1. |t Application Utility Functions -- |g 2.2. |t Resource Allocation Formulations -- |g 2.2.1. |t Max-Min Resource Allocation -- |g 2.2.2. |t Proportional Fairness -- |g 2.2.3. |t Frank Kelly Algorithm -- |g 2.3. |t Previous Studies on Resource Allocation -- |g 2.4. |t Chapter Summary -- |g 2.5. |t MATLAB Code -- |t References -- |g 3. |t Centralized Resource Allocation -- |g 3.1. |t Resource Allocation Optimization -- |g 3.1.1. |t System Model -- |g 3.2. |t Centralized Architecture -- |g 3.3. |t Existence of Global Optimal Solution -- |g 3.4. |t Centralized Solution Algorithm -- |g 3.5. |t Centralized Architecture Simulation -- |g 3.5.1. |t Rate Allocation and Bids for 10 [≥] R [≥] 200 -- |g 3.6. |t Centralized Architecture Real-World Implementation -- |g 3.7. |t Chapter Summary -- |g 3.8. |t MATLAB Code -- |t References -- |g 4. |t Distributed Resource Allocation -- |g 4.1. |t Distributed Architecture -- |g 4.1.1. |t EURA Optimization Problem -- |g 4.1.2. |t IURA Optimization Problem -- |g 4.2. |t Distributed Architecture's Global Optimal Solution -- |g 4.2.1. |t EURA Global Optimal Solution -- |g 4.2.2. |t IURA Global Optimal Solution -- |g 4.3. |t Distributed Solution Algorithm -- |g 4.3.1. |t EURA Algorithm -- |g 4.3.2. |t IURA Algorithm -- |g 4.4. |t Mathematical Equivalence -- |g 4.5. |t Distributed Architecture Simulation -- |g 4.5.1. |t Rate Allocation and Bids for 10 [≥] R [≥] 200 -- |g 4.5.2. |t Pricing for 10 [≥] R [≥] 200 -- |g 4.6. |t Benchmark -- |g 4.7. |t Chapter Summary -- |g 4.8. |t MATLAB Code -- |t References -- |g 5. |t Resource Allocation Architectures Traffic and Sensitivity Analysis -- |g 5.1. |t Traffic/Sensitivity Analysis Under UE Quantity Dynamics -- |g 5.1.1. |t Distributed Architecture with Rebidding -- |g 5.1.2. |t Distributed Architecture Without Rebidding -- |g 5.1.3. |t Centralized Architecture -- |g 5.2. |t Traffic/Sensitivity Analysis Under Application Usage Dynamics -- |g 5.2.1. |t Distributed Architecture with Rebidding -- |g 5.2.2. |t Distributed Architecture Without Rebidding -- |g 5.2.3. |t Centralized Architecture -- |g 5.3. |t Computational Complexity Considerations -- |g 5.4. |t Traffic Analysis Simulation -- |g 5.4.1. |t Transmission Overhead Analysis -- |g 5.4.2. |t Sensitivity to Application Usage Changes -- |g 5.4.3. |t Sensitivity to UE Quantity Changes -- |g 5.5. |t Chapter Summary -- |t References -- |g 6. |t Radio Resource Block Allocation -- |g 6.1. |t Introduction -- |g 6.2. |t Continuous Optimization Relaxation -- |g 6.2.1. |t Resource Block Optimization Formulation -- |g 6.2.2. |t Relaxed Optimization -- |g 6.3. |t Resource Block Optimization Solution Algorithm -- |g 6.4. |t Resource Block Simulation Results -- |g 6.4.1. |t Algorithm Convergence for R = 50 -- |g 6.4.2. |t Algorithm Convergence for 50 [≥] R [≥] 100 -- |g 6.4.3. |t Resource Block Allocation -- |g 6.5. |t Chapter Summary -- |g 6.6. |t MATLAB Code -- |t References -- |g 7. |t Spectrum-Shared Resource Allocation -- |g 7.1. |t Spectrum: A Congested and Contested Environments -- |g 7.2. |t Architecture for Fair Allocation -- |g 7.2.1. |t Congested Environment Radio Resource Allocation Optimization -- |g 7.2.2. |t Solution Algorithm -- |g 7.3. |t Practical Examples for Congested Environments and Resource Assignment -- |g 7.4. |t Radar and LTE Systems -- |g 7.4.1. |t Radar Simulation -- |g 7.4.2. |t Macro Cell, Micro Cell, and Indoor LTE Simulation -- |g 7.4.3. |t Propagation Model -- |g 7.4.4. |t Radar Interference to Macro Cell LTE -- |g 7.4.5. |t Radar to Outdoor Small Cell LTE UL Interference -- |g 7.4.6. |t Radar Interference to Indoor Small Cell LTE -- |g 7.5. |t Shared-Spectrum Resource Allocation -- |g 7.6. |t Chapter Summary -- |g 7.7. |t MATLAB Code -- |t References -- |g 8. |t Delay-Based Backhaul Modeling -- |g 8.1. |t Introduction -- |g 8.2. |t Theoretical Background -- |g 8.2.1. |t Hidden Markov Processes -- |g 8.2.2. |t Forward-Backward Algorithm -- |g 8.2.3. |t Quantization -- |g 8.3. |t System Model for Backhaul QoS -- |g 8.3.1. |t Delay-Based HMP Modeling of Networks -- |g 8.3.2. |t Quantization and Fidelity -- |g 8.4. |t End-to-End QoS and Delay-Based Backhaul Modeling -- |g 8.5. |t Experiments Results -- |g 8.5.1. |t NS2 Experiments -- |g 8.5.2. |t Internet Experiments -- |g 8.5.3. |t Numerical Experiments -- |g 8.6. |t Chapter Summary -- |g 8.7. |t MATLAB -- |g 8.7.1. |t Dataset Generation from ARM Processes -- |g 8.7.2. |t Dataset Generation from NS2 -- |g 8.7.3. |t LBG Quantization -- |g 8.7.4. |t Uniform Quantization -- |g 8.7.5. |t μ-Law Quantization -- |g 8.7.6. |t Discrete Time Discrete Observation Bivariate HMP -- |g 8.7.7. |t Discrete Time Discrete Observation Conventional HMP -- |g 8.7.8. |t Discrete Time Exponential Observation HMP -- |g 8.7.9. |t Discrete Time Discrete Observation Bivariate HMP Validation -- |g 8.7.10. |t Discrete Time Discrete Observation Conventional HMP Validation -- |g 8.7.11. |t Discrete Time Exponential Observation HMP Validation -- |t References -- |g 9. |t Book Summary -- |g 9.1. |t Future Trajectory. |
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