Spectral, Energy and Computation Efficiency in Future 5G Wireless Networks

Wireless technology has revolutionized the way people communicate. From first generation, or 1G, in the 1980s to current, largely deployed 4G in the 2010s, we have witnessed not only a technological leap, but also the reformation of associated applications. It is expected that 5G will become commercially available in 2020. 5G is driven by ever-increasing demands for high mobile traffic, low transmission delay, and massive numbers of connected devices. Today, with the popularity of smart phones, intelligent appliances, autonomous cars, and tablets, communication demands are higher than ever, especially when it comes to low-cost and easy-access solutions. Existing communication architecture cannot fulfill 5G’s needs. For example, 5G requires connection speeds up to 1,000 times faster than current technology can provide. Also, from transmitter side to receiver side, 5G delays should be less than 1ms, while 4G targets a 5ms delay speed. To meet these requirements, 5G will apply several disruptive techniques. We focus on two of them: new radio and new scheme. As for the former, we study the non-orthogonal multiple access (NOMA) and as for the latter, we use mobile edge computing (MEC). Traditional communication systems allow users to communicate alternatively, which clearly avoids inter-user interference, but also caps the connection speed. NOMA, on the other hand, allows multiple users to transmit simultaneously. While NOMA will inevitably cause excessive interference, we prove such interference can be mitigated by an advanced receiver side technique. NOMA has existed on the research frontier since 2013. Since that time, both academics and industry professionals have extensively studied its performance. In this dissertation, our contribution is to incorporate NOMA with several potential schemes, such as relay, IoT, and cognitive radio networks. Furthermore, we reviewed various limitations on NOMA and proposed a more practical model. In the second part, MEC is considered. MEC is a transformation from the previous cloud computing system. In particular, MEC leverages powerful devices nearby and instead of sending information to distant cloud servers, the transmission occurs in closer range, which can effectively reduce communication delay. In this work, we have proposed a new evaluation metric for MEC which can more effectively leverage the trade-off between the amount of computation and the energy consumed thereby. A practical communication system for wearable devices is proposed in the last part, which combines all the techniques discussed above. The challenges for wearable communication are inherent in its diverse needs, as some devices may require low speed but high reliability (factory sensors), while others may need low delay (medical devices). We have addressed these challenges and validated our findings through simulations

Wireless-powered cooperative MIMO NOMA networks: Design and performance improvement for cell-edge users

In this paper, we study two transmission scenarios for the base station (BS) in cellular networks to serve the far user, who is located at the cell-edge area in such a network. In particular, we show that wireless-powered non-orthogonal multiple access (NOMA) and the cell-center user in such a model can harvest energy from the BS. To overcome disadvantages of the cell-edge user due to its weak received signal, we fabricate a far NOMA user with multiple antennas to achieve performance improvement. In addition, the first scenario only considers a relay link deployed to forward signals to a far NOMA user, while both direct links and relay links are generally enabled to serve a far user in the second scenario. These situations, together with their outage performance, are analyzed and compared to provide insights in the design of a real-multiple-antenna NOMA network, in which the BS is also required to equip multiple antennas for robust quality of transmission. Higher complexity in computations is already known in consideration of outage metrics with respect to performance analysis, since the system model employs multiple antennas. To this end, we employ a transmit antenna selection (TAS) policy to formulate closed-form expressions of outage probability that satisfies the quality-of-service (QoS) requirements in the NOMA network. Our simulation results reveal that the performance of the considered system will be improved in cases of higher quantity of transmit antennas in dedicated devices. Finally, the proposed design in such a NOMA system cannot only ensure a downlink with higher quality to serve a far NOMA user, but also provide significant system performance improvement compared to a traditional NOMA networks using a single antenna.Web of Science83art. no. 32

New Approaches Using Cognitive Radio in Green Networking

The green networks are energy-efficient network architectures and we consider them as the basis of the wireless communication optimizing energy usage. Indeed, future communication technologies are moving in this direction, meaning that they will be less energy-intensive and, in some cases, even energy self-sufficient. Specifically, cognitive radio (CR) networks, cooperative relay networks, and non-orthogonal multiple access (NOMA) techniques have been considered as effective means to facilitate energy harvesting (EH) and a power spectrum allocation for the minimization of total transmit power, hence, making the wireless communication greener. The dissertation consists of three research sections corresponding to the aims. The first aim deals with an radio frequency (RF) wireless energy transfer model for D2D systems. In order to harvest more energy, a multiple-antenna base station and a power beacon are adopted for the D2D transmission network. We derive expressions outage probability in closed-forms. Further, independent simulations are used to validate the exactness of the theoretical expressions. In the second aim, new cooperative system models are proposed and studied. To reach the second aim, the secondary source acts as a relay and employs Amplify and Forward (AF) mode to serve distant NOMA users under a given interference constraint. To provide a detailed examination of the system performance metrics, we derived closed-form formulas for the outage probability and average throughput of the multi-users in the presence of interference constraints. In the last aim of the dissertation, we designed a new system model for a hybrid satellite-terrestrial cognitive network (HSTCN) relying on NOMA interconnecting a satellite and multiple terrestrial nodes. Reliability and security of transmission were studied to minimize the total transmit power. To reach the third aim, we examined the following performance factors: outage probability, hardware impairment, intercept probability, and average throughput. The novel closed-forms expressions of these performance factors are derived. The last but not at least, we simulated the new HSTCN system model. The achieved results figured that the new proposed approaches make it possible to take into account service quality requirements and are applicable in future green networking.Zelené sítě jsou energeticky efektivní síťové architektury a považujeme je za základ bezdrátové komunikace optimalizující spotřebu energie. Tímto směrem se ubírají budoucí komunikační technologie, což znamená, že budou méně energeticky náročné a v některých případech dokonce energeticky soběstačné. Kognitivní rádiové (CR) sítě, kooperativní relay sítě a neortogonální vícenásobné přístupové (NOMA) techniky jsou považovány za účinný prostředek k usnadnění získávání energie (EH) a přidělování výkonového spektra pro minimalizaci celkového vysílacího výkonu, díky čemuž je bezdrátová komunikace zelenější. Disertační práce se skládá ze tří výzkumných částí odpovídajících cílům. První cíl se zabývá modelem bezdrátového přenosu radiofrekvenční (RF) energie pro systémy D2D. Aby bylo možné získat více energie, jsou pro přenosovou D2D síť použity základnové stanice s více anténami a napájecím radiomajákem. Pro navržený model jsou odvozeny pravděpodobnosti výpadků, kdy tyto výrazy jsou v uzavřené formě. Dále jsou k ověření platnosti získaných teoretických výrazů použity nezávislé simulace. Ve druhém cíli jsou navrženy a zkoumány nové modely kooperativního systému. Aby bylo dosaženo druhého cíle, sekundární zdroj funguje jako relay uzel a využívá režim AF (Amplify and Forward), který slouží vzdáleným NOMA uživatelům za specifických interferenčních podmínek. Abychom poskytli podrobné zhodnocení výkonnostních metrik systému, odvodili jsme vztahy v uzavřené formě pro pravděpodobnost výpadků a průměrnou propustnost více uživatelů za přítomnosti interferenčních omezení. V posledním cíli disertační práce jsme navrhli nový systémový model pro hybridní satelitně-terestrickou kognitivní síť (HSTCN) založenou na neortogonálním vícenásobném přístupu (NOMA) propojující satelit a více terestrických uzlů. Zkoumána byla spolehlivost a zabezpečení přenosu s důrazem na minimalizaci celkového vysílacího výkonu. Pro dosažení třetího cíle jsme zkoumali následující výkonnostní faktory: pravděpodobnost výpadku, poškození hardwaru, pravděpodobnost zachycení a průměrnou propustnost. Pro tyto výkonnostní faktory jsou odvozeny v uzavřených formách nové výrazy. V neposlední řadě jsme rovněž simulovali nový systémový HSTCN model. Dosažené výsledky potvrdily, že nově navržené přístupy umožňují zohledňovat požadavky na kvalitu služeb a jsou použitelné v budoucích zelených sítích.440 - Katedra telekomunikační technikyvyhově

Energy-efficient non-orthogonal multiple access for wireless communication system

Non-orthogonal multiple access (NOMA) has been recognized as a potential solution for enhancing the throughput of next-generation wireless communications. NOMA is a potential option for 5G networks due to its superiority in providing better spectrum efficiency (SE) compared to orthogonal multiple access (OMA). From the perspective of green communication, energy efficiency (EE) has become a new performance indicator. A systematic literature review is conducted to investigate the available energy efficient approach researchers have employed in NOMA. We identified 19 subcategories related to EE in NOMA out of 108 publications where 92 publications are from the IEEE website. To help the reader comprehend, a summary for each category is explained and elaborated in detail. From the literature review, it had been observed that NOMA can enhance the EE of wireless communication systems. At the end of this survey, future research particularly in machine learning algorithms such as reinforcement learning (RL) and deep reinforcement learning (DRL) for NOMA are also discussed

Energy-Efficient NOMA Enabled Heterogeneous Cloud Radio Access Networks

Heterogeneous cloud radio access networks (H-CRANs) are envisioned to be promising in the fifth generation (5G) wireless networks. H-CRANs enable users to enjoy diverse services with high energy efficiency, high spectral efficiency, and low-cost operation, which are achieved by using cloud computing and virtualization techniques. However, H-CRANs face many technical challenges due to massive user connectivity, increasingly severe spectrum scarcity and energy-constrained devices. These challenges may significantly decrease the quality of service of users if not properly tackled. Non-orthogonal multiple access (NOMA) schemes exploit non-orthogonal resources to provide services for multiple users and are receiving increasing attention for their potential of improving spectral and energy efficiency in 5G networks. In this article a framework for energy-efficient NOMA H-CRANs is presented. The enabling technologies for NOMA H-CRANs are surveyed. Challenges to implement these technologies and open issues are discussed. This article also presents the performance evaluation on energy efficiency of H-CRANs with NOMA.Comment: This work has been accepted by IEEE Network. Pages 18, Figure

A Survey on Applications of Cache-Aided NOMA

Contrary to orthogonal multiple-access (OMA), non-orthogonal multiple-access (NOMA) schemes can serve a pool of users without exploiting the scarce frequency or time domain resources. This is useful in meeting the future network requirements (5G and beyond systems), such as, low latency, massive connectivity, users' fairness, and high spectral efficiency. On the other hand, content caching restricts duplicate data transmission by storing popular contents in advance at the network edge which reduces data traffic. In this survey, we focus on cache-aided NOMA-based wireless networks which can reap the benefits of both cache and NOMA; switching to NOMA from OMA enables cache-aided networks to push additional files to content servers in parallel and improve the cache hit probability. Beginning with fundamentals of the cache-aided NOMA technology, we summarize the performance goals of cache-aided NOMA systems, present the associated design challenges, and categorize the recent related literature based on their application verticals. Concomitant standardization activities and open research challenges are highlighted as well

Enabling non-linear energy harvesting in power domain based multiple access in relaying networks: Outage and ergodic capacity performance analysis

The Power Domain-based Multiple Access (PDMA) scheme is considered as one kind of Non-Orthogonal Multiple Access (NOMA) in green communications and can support energy-limited devices by employing wireless power transfer. Such a technique is known as a lifetime-expanding solution for operations in future access policy, especially in the deployment of power-constrained relays for a three-node dual-hop system. In particular, PDMA and energy harvesting are considered as two communication concepts, which are jointly investigated in this paper. However, the dual-hop relaying network system is a popular model assuming an ideal linear energy harvesting circuit, as in recent works, while the practical system situation motivates us to concentrate on another protocol, namely non-linear energy harvesting. As important results, a closed-form formula of outage probability and ergodic capacity is studied under a practical non-linear energy harvesting model. To explore the optimal system performance in terms of outage probability and ergodic capacity, several main parameters including the energy harvesting coefficients, position allocation of each node, power allocation factors, and transmit signal-to-noise ratio (SNR) are jointly considered. To provide insights into the performance, the approximate expressions for the ergodic capacity are given. By matching analytical and Monte Carlo simulations, the correctness of this framework can be examined. With the observation of the simulation results, the figures also show that the performance of energy harvesting-aware PDMA systems under the proposed model can satisfy the requirements in real PDMA applications.Web of Science87art. no. 81

Energy Efficient Uplink Transmission in Cooperative mmWave NOMA Networks with Wireless Power Transfer

In 5G wireless networks, cooperative non-orthogonal multiple access (NOMA) and wireless power transfer (WPT) are efficient ways to improve the spectral efficiency (SE) and energy efficiency (EE). In this paper, a new cooperative NOMA scheme with WPT is proposed, where EE optimization with a constrained maximum transmit power and minimum required SE is considered for the user grouping and transmit power allocation of users. We obtain a sub-optimal solution by decoupling the original problem in two sub-problems: an iterative algorithm is considered for the user grouping, while, in addition, we utilize the Bat Algorithm (BA) for solving the power allocation problem, where BA was proved to be able to achieve a higher accuracy and efficiency with respect to other meta-heuristic algorithms. Furthermore, to validate the performance of the proposed system, analytical expressions for the energy outage probability and outage probability of users are derived, confirming the effectiveness of the simulation results. It is demonstrated that the proposed cooperative NOMA with WPT offers a considerable improvement in terms of SE and EE of the network compared to other methods. Finally, the effectiveness of BA in solving the EE optimization problem is demonstrated through a high convergence speed by comparing it with other methods