[Paper Review] Generalized Optimal Two-way Relays Subsets Pairings in Cloud-based Region Cognitive Networks

He Huang, Chaowei Yuan|arXiv (Cornell University)|Sep 11, 2019

Cooperative Communication and Network Coding42 references4 citations

TL;DR

This paper proposes a generalized optimal two-way relay subset pairing model in cloud-based cognitive networks, classifying relays into three functional subsets (A: receive-only, B: receive-and-forward, C: transmit-only) to minimize outage probability. The proposed algorithm achieves superior reliability by optimizing subset pairings, significantly reducing outage probability compared to classical schemes, as validated by simulations.

ABSTRACT

Communication reliability improving is one of most important research requirements in cognitive networks, as 5G communications technology rapidly develop nowadays. In this paper, we propose generalized optimal cloud-based region relays subsets paring model in underlay dual-hop cognitive networks, this unified model reveals three relays nodes characteristics of cloud-based cooperative networks in the nearby area- A subset, only needs receiving for first hop, B subset, just receive and forward, C subset, only forwarding. In addition, this generalized model can be converted into various classical relay selection algorithms when A, B and C subsets are taken as special selection values [Table II]. Furthermore, we put forward optimal relays subsets pairings and replacement algorithm flowchart to improve minimum outage probability (OP) for communication reliability, and prove that optimal relays subsets pairings (A, B, C) will better guarantee reliability of communication, comparing other popular relays selection schemes. Simulation results show that optimal relays paired subsets are exist and this generalized algorithm enormously reduces OP, comparing other selection algorithms.

Motivation & Objective

• To address the critical need for improved communication reliability in 5G-enabled cognitive networks.
• To model and optimize relay functionality in underlay dual-hop cognitive networks using a unified subset classification.
• To reduce outage probability (OP) through optimal pairing of relay subsets (A, B, C) in cloud-based region cognitive networks.
• To generalize classical relay selection algorithms as special cases of the proposed model.
• To develop a systematic algorithm flowchart for optimal relay subset pairings and replacements.

Proposed method

• The paper introduces a unified model that divides relay nodes into three functional subsets: A (receive-only), B (receive-and-forward), and C (transmit-only), based on their roles in two-way communication.
• It formulates a generalized relay selection framework that can be reduced to classical schemes by setting specific values for subsets A, B, and C.
• An optimal relay subset pairing and replacement algorithm is designed to minimize the minimum outage probability (OP) through iterative selection and replacement of relay groups.
• The algorithm uses a flowchart-based approach to dynamically select and reconfigure relay subsets based on channel state information and reliability metrics.
• Theoretical analysis proves that the (A, B, C) pairing configuration achieves lower OP than conventional schemes.
• Simulations validate the existence of optimal subset pairings and demonstrate significant OP reduction across various network conditions.

Experimental results

Research questions

• RQ1 Can a generalized relay subset pairing model be formulated to unify and extend classical relay selection algorithms in cognitive networks?
• RQ2 How does the functional classification of relays into A, B, and C subsets affect the outage probability in two-way cloud-based cognitive networks?
• RQ3 What is the optimal configuration of relay subsets (A, B, C) that minimizes outage probability and enhances communication reliability?
• RQ4 Can the proposed algorithm dynamically identify and replace suboptimal relay pairs to maintain low outage probability?
• RQ5 How does the generalized model compare quantitatively in performance to existing relay selection schemes?

Key findings

• The proposed generalized model successfully unifies multiple classical relay selection algorithms as special cases by adjusting the values of subsets A, B, and C.
• Optimal relay subset pairings (A, B, C) were found to exist and significantly reduce outage probability compared to other schemes.
• Simulation results confirm that the proposed algorithm achieves a lower minimum outage probability than conventional relay selection methods.
• The algorithm's flowchart-based design enables dynamic and adaptive selection of relay subsets, improving system robustness.
• The theoretical proof confirms that the (A, B, C) pairing configuration guarantees better communication reliability than alternative schemes.
• Despite the promising results, the authors withdrew the paper due to identified flaws, indicating potential issues in implementation or analysis.