138 research outputs found

    Load Aware Self-Organising User-Centric Dynamic CoMP Clustering for 5G Networks

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    Coordinated multi-point (CoMP) is a key feature for mitigating inter-cell interference, improve system throughput and cell edge performance. However, CoMP implementation requires complex beamforming/scheduling design, increased backhaul bandwidth, additional pilot overhead and precise synchronisa-tion. Cooperation needs to be limited to a few cells only due to this imposed overhead and complexity. Hence, small CoMP clusters will need to be formed in the network. In this paper, we first present a self organising, user-centric CoMP clustering algorithm in a control/data plane separation architecture (CDSA), proposed for 5G to maximise spectral efficiency (SE) for a given maximum cluster size. We further utilise this clustering algorithm and introduce a novel two-stage re-clustering algorithm to reduce high load on cells in hotspot areas and improve user satisfaction. Stage-1 of the algorithm utilises maximum cluster size metric to introduce additional capacity in the system. A novel re-clustering algorithm is introduced in stage-2 to distribute load from highly loaded cells to neighbouring cells with less load for multi-user (MU) joint transmission (JT) CoMP case. We show that unsatisfied users due to high load can be significantly reduced with minimal impact on SE

    Ubiquitous Cell-Free Massive MIMO Communications

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    Since the first cellular networks were trialled in the 1970s, we have witnessed an incredible wireless revolution. From 1G to 4G, the massive traffic growth has been managed by a combination of wider bandwidths, refined radio interfaces, and network densification, namely increasing the number of antennas per site. Due its cost-efficiency, the latter has contributed the most. Massive MIMO (multiple-input multiple-output) is a key 5G technology that uses massive antenna arrays to provide a very high beamforming gain and spatially multiplexing of users, and hence, increases the spectral and energy efficiency. It constitutes a centralized solution to densify a network, and its performance is limited by the inter-cell interference inherent in its cell-centric design. Conversely, ubiquitous cell-free Massive MIMO refers to a distributed Massive MIMO system implementing coherent user-centric transmission to overcome the inter-cell interference limitation in cellular networks and provide additional macro-diversity. These features, combined with the system scalability inherent in the Massive MIMO design, distinguishes ubiquitous cell-free Massive MIMO from prior coordinated distributed wireless systems. In this article, we investigate the enormous potential of this promising technology while addressing practical deployment issues to deal with the increased back/front-hauling overhead deriving from the signal co-processing.Comment: Published in EURASIP Journal on Wireless Communications and Networking on August 5, 201

    Self-organised multi-objective network clustering for coordinated communications in future wireless networks

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    The fifth generation (5G) cellular system is being developed with a vision of 1000 times more capacity than the fourth generation (4G) systems to cope with ever increasing mobile data traffic. Interference mitigation plays an important role in improving the much needed overall capacity especially in highly interference-limited dense deployment scenarios envisioned for 5G. Coordinated multi-point (CoMP) is identified as a promising interference mitigation technique where multiple base stations (BS) can cooperate for joint transmission/reception by exchanging user/control data and perform joint signal processing to mitigate inter-cell interference and even exploit it as a useful signal. CoMP is already a key feature of long term evolution-advanced (LTE-A) and envisioned as an essential function for 5G. However, CoMP cannot be realized for the whole network due to its computational complexity, synchronization requirement between coordinating BSs and high backhaul capacity requirement. BSs need to be clustered into smaller groups and CoMP can be activated within these smaller clusters. This PhD thesis aims to investigate optimum dynamic CoMP clustering solutions in 5G and beyond wireless networks with massive small cell (SC) deployment. Truly self-organised CoMP clustering algorithms are investigated, aiming to improve much needed spectral efficiency and other network objectives especially load balancing in future wireless networks. Low complexity, scalable, stable and efficient CoMP clustering algorithms are designed to jointly optimize spectral efficiency, load balancing and limited backhaul availability. Firstly, we provide a self organizing, load aware, user-centric CoMP clustering algorithm in a control and data plane separation architecture (CDSA) proposed for 5G to maximize spectral efficiency and improve load balancing. We introduce a novel re-clustering algorithm for user equipment (UE) served by highly loaded cells and show that unsatisfied UEs due to high load can be significantly reduced with minimal impact on spectral efficiency. Clustering with load balancing algorithm exploits the capacity gain from increase in cluster size and also the traffic shift from highly loaded cells to lightly loaded neighbours. Secondly, we develop a novel, low complexity, stable, network-centric clustering model to jointly optimize load balancing and spectral efficiency objectives and tackle the complexity and scalability issues of user-centric clustering. We show that our clustering model provide high spectral efficiency in low-load scenario and better load distribution in high-load scenario resulting in lower number of unsatisfied users while keeping spectral efficiency at comparably high levels. Unsatisfied UEs due to high load are reduced by 68.5%68.5\% with our algorithm when compared to greedy clustering model. In this context, the unique contribution of this work that it is the first attempt to fill the gap in literature for multi-objective, network-centric CoMP clustering, jointly optimizing load balancing and spectral efficiency. Thirdly, we design a novel multi-objective CoMP clustering algorithm to include backhaul-load awareness and tackle one of the biggest challenges for the realization of CoMP in future networks i.e. the demand for high backhaul bandwidth and very low latency. We fill the gap in literature as the first attempt to design a clustering algorithm to jointly optimize backhaul/radio access load and spectral efficiency and analyze the trade-off between them. We employ 2 novel coalitional game theoretic clustering methods, 1-a novel merge/split/transfer coalitional game theoretic clustering algorithm to form backhaul and load aware BS clusters where spectral efficiency is still kept at high level, 2-a novel user transfer game model to move users between clusters to improve load balancing further. Stability and complexity analysis is provided and simulation results are presented to show the performance of the proposed method under different backhaul availability scenarios. We show that average system throughout is increased by 49.9% with our backhaul-load aware model in high load scenario when compared to a greedy model. Finally, we provide an operator's perspective on deployment of CoMP. Firstly, we present the main motivation and benefits of CoMP from an operator's viewpoint. Next, we present operational requirements for CoMP implementation and discuss practical considerations and challenges of such deployment. Possible solutions for these experienced challenges are reviewed. We then present initial results from a UL CoMP trial and discuss changes in key network performance indicators (KPI) during the trial. Additionally, we propose further improvements to the trialed CoMP scheme for better potential gains and give our perspective on how CoMP will fit into the future wireless networks

    Coordinated Multi-Point Clustering Schemes: A Survey

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    The Coverage, Capacity and Coexistence of Mixed High Altitude Platform and Terrestrial Segments

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    This thesis explores the coverage, capacity and coexistence of High Altitude Platform (HAP) and terrestrial segments in the same service area. Given the limited spectrum available, mechanisms to manage the co-channel interference to enable effective coexistence between the two infrastructures are examined. Interference arising from the HAP, caused by the relatively high transmit power and the antenna beam profile, has the potential to significantly affect the existing terrestrial system on the ground if the HAP beams are deployed without a proper strategy. Beam-pointing strategies exploiting phased array antennas on the HAPs are shown to be an effective way to place the beams, with each of them forming service cells onto the ground in the service area, especially dense user areas. Using a newly developed RF clustering technique to better point the cells over an area of a dense group of users, it is shown that near maximum coverage of 96% of the population over the service area can be provided while maintaining the coexistence with the existing terrestrial system. To improve the user experience at the cell edge, while at the same time improving the overall capacity of the system, Joint Transmission – Coordinated Multipoint (JT-CoMP) is adapted for a HAP architecture. It is shown how the HAP can potentially enable the tight scheduling needed to perform JT-CoMP due to the centralisation of all virtual E-UTRAN Node Bs (eNodeBs) on the HAP. A trade-off between CINR gain and loss of capacity when adapting JT-CoMP into the HAP system is identified, and strategies to minimise the trade-off are considered. It is shown that 57% of the users benefit from the JT-CoMP. In order to enable coordination between the HAP and terrestrial segments, a joint architecture based on a Cloud – Radio Access Network (C-RAN) system is introduced. Apart from adapting a C-RAN based system to centrally connect the two segments together, the network functional split which varies the degree of the centralised processing is also considered to deal with the limitations of HAP fronthaul link requirements. Based on the fronthaul link requirements acquired from the different splitting options, the ground relay station diversity to connect the HAP to centralised and distributed units (CUs and DUs) is also considered

    Lights and Shadows: A Comprehensive Survey on Cooperative and Precoding Schemes to Overcome LOS Blockage and Interference in Indoor VLC

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    Visible light communications (VLC) have received significant attention as a way of moving part of the saturated indoor wireless traffic to the wide and unregulated visible optical spectrum. Nowadays, VLC are considered as a suitable technology, for several applications such as high-rate data transmission, supporting internet of things communications or positioning. The signal processing originally derived from radio-frequency (RF) systems such as cooperative or precoding schemes can be applied to VLC. However, its implementation is not straightforward. Furthermore, unlike RF transmission, VLC present a predominant line-of-sight link, although a weak non-LoS component may appear due to the reflection of the light on walls, floor, ceiling and nearby objects. Blocking effects may compromise the performance of the aforementioned transmission schemes. There exist several surveys in the literature focused on VLC and its applications, but the management of the shadowing and interference in VLC requires a comprehensive study. To fill this gap, this work introduces the implementation of cooperative and precoding schemes to VLC, while remarking their benefits and drawbacks for overcoming the shadowing effects. After that, the combination of both cooperative and precoding schemes is analyzed as a way of providing resilient VLC networks. Finally, we propose several open issues that the cooperative and precoding schemes must face in order to provide satisfactory VLC performance in indoor scenarios.This work has been supported partially by Spanish National Project TERESA-ADA(TEC2017-90093-C3-2-R) (MINECO/AEI/FEDER, UE), the research project GEOVEOLUZ-CM-UC3Mfunded by the call “Programa de apoyo a la realización de proyectos interdisciplinares de I+D parajóvenes investigadores de la Universidad Carlos III de Madrid 2019-2020” under the frame ofthe Convenio Plurianual Comunidad de Madrid-Universidad Carlos III de Madrid and projectMadrid Flight on Chip (Innovation Cooperative Projects Comunidad of Madrid - HUBS 2018/MadridFlightOnChip). Additionally, it has been supported partially by the Juan de la CiervaIncorporación grant IJC2019-040317-I and Juan de la Cierva Formación grant (FJC2019-039541-I/AEI/10.13039/501100011033)

    Joint User‑Centric Clustering and Multi‑cell Radio Resource Management in Coordinated Multipoint Joint Transmission

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    Coordinated multipoint joint transmission (JT-CoMP) is a promising solution to address inter-cell interference in dense future wireless networks due its strength in converting interfering signals into useful signals, thereby enhancing capacity especially at the cell edge. However, allowing all user equipments (UEs) to operate using the JT-CoMP mode reduces the availability of radio resources. This paper develops an efficient algorithm that can identify which UEs will benefit from operating in a JT-CoMP mode and how to efficiently allocate radio resources from multiple base stations. Joint user-centric JT-CoMP clustering and multi-cell resource management is used in two steps where user-centric clusters are constructed as a first step and according to the clustering results obtained, resources are assigned. This paper also provides a new user-centric clustering approach that allows a user to utilize the JT-CoMP technique only if JT-CoMP boosts its rate above a certain threshold level. A multi-cell resource allocation scheme that can address the resource mismatching problem between cooperative BSs that happens due to load imbalance is proposed. Simulation results show that the proposed user-centric clustering algorithm outperforms the traditional power level difference scheme in terms of the system’s overall throughput as well as the throughput of cell-edge users. Also, results show that the performance of JT-CoMP is mainly affected by the user-centric approach and the amount of physical radio resources assigned to CoMP UEs
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