On the performance of interference subspace rejection for next generation multicarrier CDMA
Bibliographic record
Abstract
A multicarrier-CDMA receiver with full interfer- ence suppression capabilities, named multi-carrier interference subspace rejection (MC-ISR), has recently been proposed and assessed by simulations for high-rate transmissions over next- generation CDMA systems. In this paper, we derive a link/system- level performance analysis of MC-ISR based on the Gaussian assumption (GA) and validate it by simulations. In addition, we provide a comparative study of the two potential next- generation multicarrier CDMA air-interface configurations: MT- CDMA and MC-DS-CDMA. Simulations show that for both DBPSK and DQPSK modulations, MT-CDMA has the best link- level performance and the highest throughput. With two receiving antennas and nine MT-CDMA subcarriers in 5 MHz bandwidth, MC-ISR provides about 1.4 bps/Hz at low mobility for DBPSK, i.e., an increase of 170% in spectrum efficiency over a DS-CDMA system with MRC. I. INTRODUCTION Although multi-carrier (MC)-CDMA systems are promis- ing, challenges remain before they can achieve their full potential. One of the major obstacles in detecting MC-CDMA signals is interference. The multiple access interference (MAI) and the inter-symbol interference (ISI), which are inherited from conventional DS-CDMA, affect likewise the performance of MC-CDMA systems. In addition, MC-CDMA capacity is limited by the inter-carrier interference (ICI) due to the use of multicarrier modulation. Indeed, the imperfect frequency down-conversion due to the instability of local oscillators combined with the multipath effect disturbs the subcarriers orthogonality thereby causing ICI. Since MC-CDMA systems also contain a DS-CDMA com- ponent, traditional multiuser detection techniques can be per- formed on each carrier with some form of adaptation. An efficient multiuser detection technique, denoted interference subspace rejection (ISR), first proposed for DS-CDMA (1), has been recently developed for multicarrier systems (2). The performance of multi-carrier (MC)-ISR was evaluated there through simulations using very realistic link-level simulation setups that take into account time and frequency mismatch, imperfect power control, channel identification errors etc. Simulation results confirm the net advantage of the full in- terference suppression capabilities of MC-ISR. In this paper, we develop a theoretical link/system-level performance analysis of MC-ISR based on the Gaussian assumption (GA), under the condition of perfect channel identification. In addition, we provide a comparative study of the two potential next-generation multicarrier CDMA air- interface configurations: MT-CDMA and MC-DS-CDMA.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".