Cooperative communication for relay and multiple access channels: Design, optimization and performance analysis
Bibliographic record
Abstract
In modern and future cellular networks such as Long-Term Evolution-Advanced (LTE-A)and 5G systems, cooperative communication can be deployed as an efficient method to improvesystem performance and meet the high-speed data transmission needs of multimediaservices. This thesis studies cooperation in the multiple access channel (MAC) setting,which includes the relay channel (RC) setting as a special case. These cooperative settingsapply to uplink transmission in cellular networks and form the basis to improve the widenetwork performance.The thesis proposes a time-division half-duplex scheme for the MAC with transmittercooperation (MAC-TC). The proposed scheme divides each transmission frame into threephases with variable durations. The two user equipments (UEs) partially exchange theirinformation in the first two phases, then cooperatively and coherently transmit to the basestation (BS) in the third phase, i.e., each UE performs a partial decode-forward (pDF) ofthe other UE information. The BS then performs joint decoding using the signals receivedin all three phases. After designing the scheme for the discrete memoryless channel (DMC),the thesis applies it to the Gaussian channel, derives its optimal resource allocations formaximum throughput and studies the outage performance over fading links. Comparedwith existing schemes, the proposed scheme improves throughput and outage performance,which makes it appealing for deployment in future cellular networks by utilizing the device-to-device (D2D) and infrastructure modes in the uplink transmission.The proposed scheme is near capacity-achieving when the cooperative links are strongerthan the direct links. Compared to existing schemes, this scheme achieves the same orbetter spectral efficiency with simpler signals and shorter decoding delay. By analyzingthe KKT optimality conditions for the maximum transmission rate, the thesis shows thatas the inter-user link qualities increase, the optimal scheme moves from no cooperation topartial then to full cooperation, in which the users fully exchange their information. Theoptimal power allocation to achieve the maximum throughput is analytically derived.The thesis further formulates the outage probability of the cooperative scheme overRayleigh fading channels assuming full channel state information (CSI) at receivers andlimited CSI at transmitters. Results show that cooperation can significantly reduce outageprobabilities and achieve the full diversity order despite additional outages at the UEs. Thethesis considers the RC setting in detail and analytically derives the outage performance for the coherent pDF relaying. Results show that the proposed scheme outperforms the existingschemes since it employs coherent transmission and joint decoding at the destination.Last, the thesis proposes a MAC with a joint source-destination cooperation (MAC-SDC)scheme that also engages the BS in cooperation by employing quantize-forward relaying.In this scheme, the users exchange their information not only through the cooperativelinks as in the MAC-TC, but also via the feedback links from the BS. Results showachievability improvement especially when the cooperative links are marginally strongerthan direct links. Moreover, for the RC setting, the thesis proves that the proposed schemeasymptotically achieves capacity by reaching the cutset bound as BS power increases.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".