Impact of Hardware Impairment on the Uplink SIMO Cooperative NOMA With Selection Relay Under Imperfect CSI
Bibliographic record
Abstract
Non-orthogonal multiple access (NOMA) has emerged as a promising solution for enabling massive connectivity in future wireless networks. A great deal of research has extensively considered the implementation of the NOMA with other technologies such as multi-antenna and cooperative communications. Most of the previous studies focused on investigating the downlink NOMA networks, while the uplink papers received relatively less attention. Besides, the majority of the current studies on uplink NOMA schemes have neglected practical limitations. Motivated by this, we investigate the uplink single-input multiple-output cooperative NOMA (SIMO-CNOMA) performance in the presence of hardware impairment (HWI), imperfect channel state information (ipCSI), and imperfect successive interference cancellation (ipSIC). We expand the scope of the proposed system to encompass multiple relay schemes, within which the selection relay technique is executed. We derive the outage probability (OP) and the system throughput of the considered system over the Rayleigh fading channels. In this respect, we provide performance analysis for different combinations of relays and antennas. The OP and system throughput analytical expressions are validated through computer simulations. In addition, the effects of HWI, ipCSI, and ipSIC on the performance of the uplink SIMO-CNOMA are discussed. The results show that the system’s performance can be improved with an increase in the relays and antenna numbers. Also, there is an error floor at the high signal-to-noise ratio (SNR) in ideal conditions (i.e., in the absence of HWI, ipCSI, and ipSIC), and the error floor is increased in non-ideal conditions (i.e., in the presence of HWI, ipCSI, and ipSIC). The arbitrary number of users in the presence of non-ideal conditions increases the error and reduces the system’s performance. Finally, although the performance gains obtained through the use of multiple antennas and relays, the adverse effects of HWI, ipCSI, and ipSIC on system performance cannot be avoided.
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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 | 0.001 |
| 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".