The next-generation wireless networks are expected to support a number of computation-intensive and delay-sensitive applications such as virtual reality (VR), autonomous driving, telesurgery and unmanned aerial vehicles (UAVs). Since many devices are computation and power limited, mobile edge computing (MEC) has been deemed as a promising way to enhance computation service. In this paper, we propose a novel cooperative MEC that exploits the combination of non-orthogonal multiple access (NOMA) and multiple helpers. In the proposed system featuring a user, multiple helpers and a base station (BS), the user can simultaneously offload its computation-intensive tasks to the helpers using NOMA when there is no strong direct transmission link between the user and the BS. Then, the helpers can compute and offload these tasks through NOMA. Thus, in the proposed scheme, the computation and offloading modes at the helpers are determined with respect to the optimized task offloading decision factor. The simulation results show that the proposed NOMA-based cooperative MEC significantly increases the total offloading data under the latency constraints compared to the benchmark schemes featuring one helper with strong direct transmission link.
Non-orthogonal multiple access (NOMA) based multiple-input multiple-output (MIMO), which has the potential to provide both massive connectivity and high spectrum efficiency, is considered as one of the efficient techniques for sixth generation (6G) wireless systems. In massive Internet of Things (IoT) networks, user-set selection is crucial for enhancing the overall performance of NOMA based systems when compared with orthogonal multiple access (OMA) techniques. In this paper, we propose a user-set selection algorithm for IoT uplink transmission to improve the sum data rate of the NOMA based MIMO systems. In order to exchange data between the selected IoT pairs, we propose to employ wireless physical layer network coding (PNC) to further improve the spectral efficiency and reduce the delay to fulfill the requirements of future IoT applications. Performance evaluations are provided based on both sum data rate and bit error rate for the proposed NOMA based MIMO with PNC in the considered massive IoT scenarios.
1 Abstract-Digital mobile radio is one of a digital radio standard for Professional Mobile Radio and it is commonly used for emergency services. The cell selection is very important for digital mobile radio based systems to improve system performance in terms of delay and bit error rate. In this work, we propose an efficient cell selection algorithm for Digital Mobile Radio. In the proposed algorithm, each user selects the base station according to the proposed utility value determined based on both cell load and signal-to-interference-noise ratio. The goal of the proposed algorithm is to balance the distribution of the users among the cells to reduce the waiting time for connection while establishing reliable transmission link. We illustrate the performance results for different scenarios and applications in terms of cell load, signal-to-interference-noise ratio and bit error rate.
Özetçe -Bu makalede, APCO25 telsiz sistemi için hücre seçim algoritmaları incelenmiştir. Hem baz istasyonlarının yükü hem de kullanıcıların sinyal karışım gürültü oranları göz önüne alınarak hücre seçimi gerçekleştirilmiştir. Benzetim sonuçları, data ve ses kullanıcılarının oldugu farklı senaryolar göz önüne alınarak elde edilmiştir. Önerilen hücre seçim algoritmasının, kullanıcılara daha iyi sinyal karışım gürültü oranı degerleri saglarken kullanıcıların baz istasyonlarına dengeli birşekilde atamasını da yaptıgı gösterilmiştir.Anahtar Kelimeler-APCO25, Hücre Seçim Algoritmaları Abstract-In this paper, cell selection algorithms are examined for APCO25 public safety radio networks. We present a cell selection algorithm which considers both cell load and signal to interference noise ratio. The performance results are obtained for voice and data users connected to the base stations under various scenarios. It is shown that the proposed cell selection algorithm is balanced the users among the base stations while providing better signal to interference noise ratio. Keywords-APCO25, Cell Selection Algorithms I. GİRİŞKamu güvenligi ve acil yardım kurumlarının normal, kriz ve afet zamanlarında haberleşme güvenlikleri ve kesintisizligi oldukça önemlidir. Telsiz kullanıcılarının yaratacak oldugu haberleşme trafigini karşılayacak bir sistem çözümü olarak APCO25 telsizler ön plana çıkmaktadır. APCO25 kablosuz iletişim protokolüdür ve kamu güvenligi kurumlarının sayısal radyo haberleşmesine olanak saglar. 1989 yılında APCO (Association of Public Safety Communications Officials) yöne-timinde özellikle yerel, eyalet ve federal kamu güvenligi haberleşmesi için geliştirilmiştir. Bu standart APCO Proje 25 ya da P25 olarak da bilinir [1].Kablosuz haberleşme aglarında kullanıcılara verilen servis kalitesini arttırmak için kullanıcıların hizmet alacakları baz istasyonu seçimini verimli birşekilde gerçekleştirmek, sistem başarımı açısından çok önemlidir. Hücre seçim işlemi, her kullanıcının belli bir kalitede ve sürekli birşekilde servis almasından sorumludur. Sistem yükününün dengelenmesinde ve buna baglı olarak sistemin genel performansında önemli bir rol oynar.Hücre seçiminde ve hücre geçişlerinde sinyal gücü, mesafe, sinyal gürültü oranı (SNR), sinyal-gürültü-karışım oranı (SINR), bit hata oranı (BER), trafik yogunlugu (baglı olan kullanıcı sayısı, talep edilen veri hızı vb.), öncelik ve servis kalitesi gibi parametreler ve bunların çeşitli kombinasyonları belirleyici rol oynar.Hücresel haberleşme sistemlerinde, hücre seçim işlemi için kullanılan mevcut algoritmalardan uzaklık tabanlı hücre seçim algoritmasında kullanıcı, uzaklık açısından en yakın baz istasyonuna baglanır [2]. Alınan sinyal gücü (received signal strength indicator (RSSI)) bazlı hücre seçim algoritmasında [3] ise kullanıcı, ölçtügü en yüksek alınan sinyal gücüne sahip baz istasyonuna baglanır. Bu iki hücre seçim algoritması, baz istasyonuna daha önce atanan kullanıcı yükünü göz önüne almaz.Bu bildiride, APCO25 sistemi için hücre seçim algoritmaları incelenmiştir....
Mobile edge computing (MEC) has been considered a promising technology to reduce task offloading and computing delay by enabling mobile devices to offload their computation-intensive tasks. Non-orthogonal multiple access (NOMA) is regarded as a promising method of increasing spectrum efficiency, while Massive multiple-input multiple-output (MIMO) can support a larger number of users for simultaneous offloading. These two technologies can effectively facilitate offloading and further improve the performance of MEC systems. In this work, we propose a NOMA and Massive MIMO assisted MEC system for delay-sensitive applications. Our objective is to minimize the overall computing and transmission delay under users' transmit power and MEC computing capability. Through the pairing scheme for Massive MIMO-NOMA, the users with the higher channel gain can offload all their data, while the users with the lower channel gain can offload a portion of their data to the MEC. Performance results are provided regarding to the sum data rate and overall system delay compared with the orthogonal multiple access (OMA)-MIMO based and Massive MIMO (M-MIMO) based MEC systems.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.