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Adaptive Code Allocation for Interference Exploitation on the Downlink of MC-CDMA Systems

This work presents a novel method for exploiting interference in Multi-Carrier Code Division Multiple Access (MC-CDMA) downlink systems. By reallocating user-specific codes according to instantaneous data and user cross-correlations, the proposed technique enhances the effective Signal-to-Interference-plus-Noise Ratio (SINR). The research emphasizes separating constructive and destructive interference to improve performance without additional power expenditure. Through an advanced Code-to-User Allocation (CUA) technique, the results indicate significant improvements in data detection reliability and overall communication efficiency under various conditions.

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Adaptive Code Allocation for Interference Exploitation on the Downlink of MC-CDMA Systems

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  1. Adaptive Code Allocation for Interference Exploitation on the Downlink of MC-CDMA Systems Emad Alsusa & Christos Masouros Dept. of Electrical & Electronic Engineering University of Manchester

  2. Principles of the Proposed Method • For PSK Modulation, Interference can be Separated to Constructive and Destructive • Interference Depends on Users Crosscorrelations as well as the instantaneous Data • By Reallocating the Codes According to the Current Data, the Crosscorrelations and hence Interference Amongst Users can be Manipulated • By Exploiting Constructive Interference the Effective SINR can be Increased and Performance can be Improved Without the Need to Increase Transmitted per-User Power

  3. MC-CDMA Downlink Employing post-Equalization (K users) • Received Signal at the u-th Mobile Unit (MU) at the i-th symbol period: • Decision Variable:

  4. Constructive - Destructive Interference Separation User-to-User Constructive MAI: Cumulative Constructive MAI:

  5. Constructive - Destructive Interference Separation • Instantaneous per Symbol Effective SINR:

  6. Decision Variables Distributions for pc=8 Different Allocation Patterns for K=5, L=16

  7. Code-to-User Allocation (CUA) Technique (1/9) • Create Code Sets • Evaluate Code Sets • Select Optimum Code Set • Spread and Transmit • Transmit SI • Detect SI and select the correct code • Dispread and Detect

  8. Code-to-User Allocation (CUA) Technique (2/9)

  9. Code-to-User Allocation (CUA) Technique (3/9) • Decision Variables pre-Estimation • Code Allocation Selection Criteria

  10. Code-to-User Allocation (CUA) Technique (4/9) • For Correct Dispreading According to the Updated Codes, Transmission of SI bits is Necessary • SI is Common for all Users • If Code Allocation s=7 is [3, 5, 2, 1, 4] then User k=3 Should Employ Code with Index 2 from the reference set for Correct Dispreading

  11. Code-to-User Allocation (CUA) Technique (5/9) Enhanced Received SINR, Improved Reliability Data Detection Very Sensitive to SI Errors

  12. Code-to-User Allocation (CUA) Technique (6/9) • CUA with MRC, EGC, SU- MMSE post-Equalization Performance Improvement of an Order of Magnitude Without Increase in Transmitted per-User Power Efficiency Reduction to 91% due to Transmission of Side Information (SI) Number of paths=4, K=20, L=32, pc=16

  13. Code-to-User Allocation (CUA) Technique (7/9) • CUA with EGC post-Equalization and SIC Detection Limited Improvement for Increased NC Performance Loss for Low SNR due to Unreliable SI Number of paths=4, K=20, L=32

  14. Code-to-User Allocation (CUA) Technique (8/9) • CUA with EGC Limited Improvement for Increased Number of Available Allocation Patterns (pc) Number of paths=3, K=16, L=16, SNR=7dB

  15. Code-to-User Allocation (CUA) Technique (9/9) • CUA with pre-decorrelation employing MRC Equalization Significant Performance Improvement Transmission Efficiency of 32/34=94.2% Number of paths=3, K=32, L=32, SNR=7dB

  16. Conclusions • In Conventional Systems Energy Inherent in the System is Wasted due to Data-Code Misalignment • Part of the Existent Interference can be Exploited to Enhance the Received SINR • By Optimizing the Code Allocation Amongst the Users with CUA the Constructive Component of Interference can be Maximized • Improved Received SINR without Transmitted per-User Energy Increase • Application of CUA can Enhance the Performance of a Number of Conventional MultiUser Precoding and Detection Schemes • The Dependency on SI Detection Limits the CUA Overall Performance for Low Transmitted SNR • For High SNR Values Performance Improvement of an Order of Magnitude is Attained

  17. Thank you • Questions • Comments • Suggestions

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