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INTERFERENCE MANAGEMENT
The performance limits of current mobile networks in relation to spectral efficiency and reliability will be constrained by interference-limited scenarios arising from widespread HetNet deployments [33]. The received signal at the mobile terminal is interference-limited when the total neighbouring interference power is higher than that of the noise. In this case, the effect of noise-power in system performance is considered negligible [34]. A high demand for frequency resources corresponding to the number of connected devices and UEs will intensify as the network density increases. The prevalence of many devices and cells in close proximity will inevitably lead to many interferencelimited scenarios. The consequence of interference would be the restriction on spectrum re-usability leading to tight frequency re-use. There are few categories in literature, in which to manage the surrounding interference from both the transmitter and receiver side.
Successive Interference Cancellation (SIC) Schemes
The main advantage of linear detectors is the low complexity of implementation at the sacrifice of performance. However, combining either of these linear receivers to form a bank of detectors can increase performance by employing SIC in conjunction with ZF or MMSE [97–99]. Each of the bank of linear of receivers detects one of the data streams, which is then successively cancelled from the remaining signal in the subsequent stages. The resulting outcome is that the final signal is interferencefree. However, error propagation of the detected signal in each of the stages can negatively affect the overall performance of SIC. SIC may also be integrated with ML approaches to improve detection performance [100]. A key aspect of this technique is the selection of an optimal cancellation signal sequence based either on the SNR, SINR, column-norm or received signal ordering.
TB Processing: Code Block Segmentation
The maximum supported code block size for the internal interleaver of the LTE turbo code is 6144 bits. If the total size of the transport blocks including CRC bits, are greater than the maximum allowable size, the code block undergoes segmentation into smaller, manageable pieces which are then ready to be fed into the Turbo encoder. The segmentation component is designed in such a manner that filler bits are added to varying TBs of different sizes, in order to match the required code block sizes of the turbo encoder. The CRC bits are appended to each code block in order to enhance advanced detection of correctly decoded code blocks, which essentially implies that the iterative turbo decoder can terminate early. As a result, there is a reduction in the terminal computational complexity as well as battery utilization. The Physical Downlink Control Channel (PDCCH) contains information TELECOM Paristech 41 regarding the TBS and can therefore infer the code-block size and number of code-blocks. This information aides in the decoding the TBs at the receiver side.
Table of contents :
CHAPTER 1 Introduction
1.1 Next-GenerationNetworkAdvances
1.1.1 FifthGeneration (5G)Networks
1.1.2 HeterogeneousNetworks (HetNets)
1.2 ProblemDomain
1.3 ResearchGoals
1.4 Contributions
1.5 DissertationOutline
CHAPTER 2 Background
2.1 InterferenceManagement
2.1.1 InterferenceAvoidance
2.1.2 Interference Coordination and Cooperation
2.1.3 InterferenceCancellation
2.1.4 Application inLTE
2.2 AnOverviewofMIMODetection
2.2.1 ClassicalModel
2.2.2 Non-linearDetection
2.2.3 LinearDetection
2.2.4 Successive Interference Cancellation (SIC) Schemes
2.2.5 ComplexityComparison
2.3 RelayNetworks
2.3.1 RelayTypes
2.3.2 Relaying inLTENetworks
2.4 LongTermEvolution (LTE)
2.4.1 SpecificationHighlights
2.4.2 StateofLTEAdoption
2.5 LTEPhysicalLayer
2.5.1 Downlink-SharedChannel (DL-SCH)
2.5.2 OpenAirInterfaceSimulator
2.6 Summary
I Higher-order MIMO Detection Strategies
CHAPTER 3 A Theoretic Approach to Higher-order MIMO Block Detection
3.1 Introduction
3.2 RelatedWork
3.2.1 BlockQR
3.2.2 BlockMMSE
3.3 Interference-limitedHetNetSystemModel
3.3.1 BlockQRDecomposition
3.3.2 QRDecompositionTechniques
3.3.3 BlockMMSE
3.4 Mutual InformationAnalysis
3.4.1 BlockQR
3.4.2 BlockMMSE
3.5 NumericalResults
3.6 LTESingle-UserMIMO(SU-MIMO)RateOptimization
3.6.1 BlockQRSU-MIMORateMaximisation
3.7 Conclusions
CHAPTER 4 A Practical Evaluation of Higher-order MIMO Block Detection
4.1 Introduction
4.1.1 FromAlgorithmtoBit-levelDesign
4.2 On the Complexity of the Block QR and Block MMSE Schemes
4.2.1 BlockQR
4.2.2 BlockMMSE
4.3 LTEInterference-limitedPerformance
4.4 Conclusions
II Advanced Half-Duplex Relay Networks
CHAPTER 5 Novel Half-duplex Relay Strategy for LTE networks
5.1 Introduction
5.2 PracticalHalf-duplexRelays: AState-of-the-Art
5.3 HDRelaySystemModel
5.4 SimulationTestBench
5.5 PerformanceEvaluation: StaticAWGNChannel
5.5.1 BaselineRelayScheme
5.5.2 Direct transmissionscheme (NoRelay)
5.6 Performance Evaluation: Frequency-Selective Fading Channel
5.7 Conclusions
CHAPTER 6 Conclusions and Future Outlook
6.1 Summary ofFindings
6.1.1 Part I:Higher-orderMIMODetectionStrategies
6.1.2 Part II:AdvancedHDRelayStrategy
6.2 Recommendations forFutureWork
CHAPTER 7 Résumé [Français]
7.1 Introduction
7.1.1 Objectifsde recherche
7.2 Chapitre2
7.3 Chapitre3
7.3.1 MMSEBloc
7.3.2 Modèle de système HetNet limité aux interférences
7.3.3 BlockQRDecomposition
7.3.4 RésultatsNumériques
7.3.5 Total Taux atteignable pour un seul utilisateur MIMO
7.4 Chapitre4
7.5 Chapitre5
7.5.1 Modèlede systèmede relais
7.5.2 Modèlede simulation
7.5.3 Évaluation de la performance: Statique canal AWGN
7.6 Conclusion
7.6.1 Résumédes résultats
7.7 Recommandations pour les travauxfuturs
APPENDIX A HD Relay Strategy: MCS Mapping
APPENDIX B Performance Guarantee of the Proposed Scheme
