Sidelink Destekli Hücresel Ağlarda Merkezi Çok Amaçlı İstemci–Ağ Geçidi Eşlemesi

Abstract

Mobil veri trafiğinin ve kullanıcı merkezli offloading hizmetlerinin (örneğin Wi-Fi veya sidelink tabanlı röleler) hızla artması, yalnızca sinyal gücüne dayalı basit ilişkilendirmelerin ötesine geçen ilişkilendirme mekanizmalarını gerektirmektedir. Bu çalışmada, sidelink destekli offloading kullanılan hücresel bir sistemde, tek hücreli ve Wi-Fi tabanlı cihazdan cihaza (D2D) bağlantıya sahip bir LTE ağı üzerinde somutlanan merkezi bir ağ geçidi–istemci ilişkilendirme problemini ele alıyoruz. Çok Amaçlı Kapasiteli İstemci–Ağ Geçidi İlişkilendirme Problemini (MO-CGAP) modelleyerek, bir denetleyicinin her istemciyi, ağ geçidi kapasite ve bağlantı kısıtlarına tabi olarak, en fazla bir ağ geçidine atadığını ve bunu yaparken (i) bağlı (servis verilen) istemci sayısını en büyüklediğini, (ii) elde edilen toplam veri oranını en büyüklediğini ve (iii) yük dengelemesini teşvik etmek için tam yükte çalışan ağ geçidi sayısını en aza indirdiğini varsayıyoruz. MO-CGAP’in, yalnızca toplam veri oranını en büyüklemeyi amaçlayan tek amaçlı bir varyantı için bile NP-zor olduğunu gösteriyor, bu da sezgisel çözüm yöntemlerinin kullanımını motive ediyor. MO-CGAP’e uyarlanmış iki meta-sezgisel algoritma tasarlıyoruz: probleme özgü bir kodlama, onarım ve leksikografik uygunluk (fitness) tasarımına sahip bir genetik algoritma (GA) ve aynı üç kademeli amaç önceliklendirmesini kullanan bir tavlama benzetimi (SA) şeması. Her iki yaklaşımı da, gerçekçi hücresel aşağı bağlantı ve sidelink soyutlamaları altında, farklı hotspot kümelenmeleri ve istemci yüklerine sahip dört mekânsal senaryoda dağıtık, RSSI tabanlı bir ilişkilendirme taban çizgisine karşı değerlendiriyoruz. Sayısal sonuçlar, GA ve SA’nın, RSSI tabanlı yaklaşıma kıyasla tutarlı biçimde daha yüksek bağlanabilirlik sağladığını ve orta düzey istemci yoğunluklarında, istemcileri daha dengeli dağıtarak hem toplam veri oranını iyileştirdiğini hem de tam yükte çalışan ağ geçidi sayısını azalttığını göstermektedir. GA genellikle SA’ya göre biraz daha yüksek veri hızı ve adalet (fairness) elde etmektedir. Sayısal çalışma LTE temelli olsa da, problem formülasyonu ve çözüm çerçevesi büyük ölçüde erişim teknolojisinden bağımsızdır ve 5G NR ve NR sidelink tabanlı röle mimarileri gibi modern OFDMA sistemlerine uyarlanabilir.

Keywords

• Ağ geçidi-istemci eşlemesi
• sidelink destekli yük boşaltma
• cihazdan cihaza (D2D) haberleşme
• çok amaçlı optimizasyon
• genetik algoritmalar
• benzetimli tavlama.

Supporting Institution

Bu çalışma, TÜBİTAK tarafından 115E389 numaralı proje kapsamında desteklenmiştir.

Project Number

115E389

Centralized Multi-Objective Client–Gateway Association for Sidelink-Assisted Cellular Offloading

Abstract

The rapid growth of mobile data and user-centric offloading services (e.g., Wi-Fi or sidelink-based relays) requires association mechanisms that go beyond simple signal-strength-based attachment. In this paper, we study a centralized gateway–client association problem in a cellular system with sidelink-assisted offloading, instantiated on a single-cell LTE network with Wi-Fi-based device-to-device connectivity. We model the Multi-Objective Capacitated Client-Gateway Association Problem (MO-CGAP), where a controller assigns each client to at most one gateway, subject to gateway capacity and connectivity constraints, while (i) maximizing the number of connected clients, (ii) maximizing the aggregate achieved data rate, and (iii) minimizing the number of fully loaded gateways to promote load balancing. We show that MO-CGAP is NP-hard even for a single-objective throughput-maximization variant, which motivates heuristic solution methods. We design two metaheuristic algorithms tailored to MO-CGAP: a genetic algorithm (GA) with a problem-specific encoding, repair, and lexicographic fitness design, and a simulated annealing (SA) scheme that uses the same three-tier objective prioritization. Both are evaluated against a distributed RSSI-based association baseline under realistic cellular downlink and sidelink abstractions, across four spatial scenarios with varying hotspot clustering and different client loads. Numerical results show that GA and SA consistently achieve higher connectivity than the RSSI-based baseline and, for moderate client densities, also improve aggregate throughput and reduce the number of fully loaded gateways by distributing clients more evenly. GA typically yields slightly better throughput and fairness than SA. Although the numerical study is LTE-based, the problem formulation and solution framework are largely radio-access-agnostic and can be adapted to modern OFDMA systems such as 5G NR and NR sidelink-based relay architectures.

Keywords

• Gateway-client association
• sidelink-assisted offloading
• device-to-device (D2D) communication
• multi-objective optimization
• genetic algorithms
• simulated annealing.

Supporting Institution

This work was supported by TUBITAK under Grant 115E389.

Project Number

115E389

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