Relay-Based Clustering Method for Interference Management in Heterogeneous Wireless Cellular Network

Femtocell is one of solutions to improve quality of services and network capacity for users in indoor areas. Radio resources used by femtocells are shared from macrocell network, thus it saves the use of frequency spectrum. However, one of problems in deploying femtocells within coverage area of macrocells is interference due to radio resources sharing between femtocells and macrocells. It creates interferences called as cross-tier (macrocell-femtocell/femtocell-macrocell) and co-tier (macrocell-macrocell/femtocell-femtocell) interferences. This paper proposes a relay-based clustering method to mitigate interference in femtocells located in the whole edge area of macrocell and the cell edge area of sectorized macrocells. Relay nodes are deployed statically (fixed location) in the neighboring macrocell area. Relay node will recruit their members based on the shortest distance. Certain relay node’s members do not need to transmit large amounts of power to enhanced Node B (eNB), such that interference from Macrocell User Equipment (MUE) to Home enhanced Node B (HeNB) can be minimized. Simulation experiments has been carried out and optimistic results for the sectorized macrocells scenario show that Signal-to-Interference-plus-Noise-Ratio (SINR) of femtocells for the conventional system that does not reach the targeted SINR of 20 dB is 87%. Meanwhile, after applying the relay-based clustering method, SINR value of femtocells below or equal to 20 dB reaches 72%. Optimistic results for throughput and Bit Error Rate (BER) show improvement of 15% and 14%, respectively. It has been shown that the relay-based clustering method can provide better performance compared to the conventional system even for femtocells densely deployed.

Evaluation of cell load of the LTE network based on control information decoding

Cell load evaluation is the one of the tools used for the development of methods to increase quality of service (QoS) in cellular networks. For instance, the analysis of mobile traffic usage can be used for network optimization and management in terms of radio resources. Existing assessing methods, such as drive tests or passive evaluations based on analysis of physical channel indicators are either unreliable, inaccurate, or inconvenient. A cell load evaluation method based on decoding and analysing the control channels is presented. The method can reliably monitor the resource allocations and the throughput in a public mobile cell. A real LTE signal recorded from the eNodeB using software defined radio was analysed. The main indicators of the cell were determined, including the efficiency of using resource blocks, the number of active users, and the cell’s throughput. The accuracy of the algorithm was also evaluated in this paper.

Cross-Cycled Uplink Resource Allocation over NB-IoT

Before each user equipment (UE) can send data using the narrowband physical uplink shared channel (NPUSCH), each UE should periodically monitor a search space in the narrowband physical downlink control channel (NPDCCH) to decode a downlink control indicator (DCI) over narrowband Internet of Things (NB-IoT). This monitoring period, called the NPDCCH period in NB-IoT, can be flexibly adjusted for UEs with different channel qualities. However, because low-cost NB-IoT UEs operate in the half-duplex mode, they cannot monitor search spaces in NPDCCHs and transmit data in the NPUSCH simultaneously. Thus, as we observed, a percentage of uplink subframes will be wasted when UEs monitor search spaces in NPDCCHs, and the wasted percentage is higher when the monitored period is shorter. In this paper, to address this issue, we formulate the cross-cycled resource allocation problem to reduce the consumed subframes while satisfying the uplink data requirement of each UE. We then propose a cross-cycled uplink resource allocation algorithm to efficiently use the originally unusable NPUSCH subframes to increase resource utilization. Compared with the two resource allocation algorithms, the simulation results verify our motivation of using the cross-cycled radio resources to achieve massive connections over NB-IoT, especially for UEs with high channel qualities. The results also showcase the efficiency of the proposed algorithm, which can be flexibly applied for more different NPDCCH periods.

A Multi-Beam Satellite Cooperative Transmission Scheme Based on Resources Optimization and Packets Segmentation

Multi-beam satellite communication systems are promising architectures in the future. A packet is transmitted by multi-satellite and multi-beam cooperatively, which can provide efficient spectrum utilization, improve system throughput, and guarantee Quality of Services (QoS). In multi-beam satellite communication systems, multi-layer and multi-dimensional radio resources change dynamically, which leads to the discontinuity of optimal resources and the lack of mapping balance between packets and radio resources. To deal with these problems, we propose a cross-layer and cross-dimension radio resources optimization model based on the weighted discrete firefly algorithm and an adaptive packet segmentation scheme based on the irregular gradient algorithm. The cross-layer and cross-dimension radio resources optimization model based on the weighted discrete firefly algorithm simulates cross-layer and cross-dimension optimization for the high-dynamic and multi-dimensional radio resources by considering the channel state information (CSI) and QoS in the multi-beam satellite communication system. The optimal resources are taken as the weight of irregular gradient algorithm to segment packets and map packets to radio resources, which can realize the mapping balance between packets and radio resources and ensure the efficiency and reliability of communication. The simulations show that the new transmission scheme improves the normalized system throughput and user satisfaction index by 18.7% and 6.2%, respectively.

Reducing Interference via Link Adaptation in Delay-Critical Wireless Networks

One of the current 6G wireless networks research's trends is to investigate short distance and dense scenarios, where users are locally connected in sub-networks. Such use case is critical to support the advances of industrial internet of things or Industry 4.0, e.g. connecting an entire group of sensors and actuators of a robot. Therefore, schemes that can properly manage the interference must be deployed in practical systems to allow the promised performance advances of 6G . Targeting these high density scenarios, we describe the Power Optimization for Low Interference and Throughput Enhancement (POLITE) paradigm for link adaptation and power allocation, which leverages available radio resources to stabilize and reduce the interference. The baseline link adaptation schemes are compared with POLITE in their performance in a 3GPP -calibrated system level simulator for industrial scenarios. As services in industrial environments require high reliability under constrained delays, we propose different delay-aware formulations in the POLITE design. In this work we provide solutions both for relaxed delay requirements and for latency critical traffic, whose delay must be minimized. In particular, in the latter case, we propose also modifications of user selection and resource allocation procedures to further improve the reliability and latency. Simulation results prove the benefits of POLITE in terms of increased throughput, fulfillment of relaxed and delay-critical requirements, with an overall reduced transmit power compared to the current baseline link adaptation schemes.

Association Control Based Load Balancing in Wireless Cellular Networks Using Preamble Sequences

<p>The efficient allocation and use of radio resources is crucial for achieving the maximum possible throughput and capacity in wireless networks. The conventional strongest signal-based user association in cellular networks generally considers only the strength of the signal while selecting a BS, and ignores the level of congestion or load at it. As a consequence, some BSs tend to suffer from heavy load, while their adjacent BSs may carry only light load. This load imbalance severely hampers the network from fully utilizing the network capacity and providing fair services to users. In this thesis, we investigate the applicability of the preamble code sequence, which is mainly used for cell identification, as an implicit information indicator for load balancing in cellular networks. By exploiting the high auto-correlation and low cross-correlation property among preamble sequences, we propose distributed load balancing schemes that implicitly obtain information about the load status of BSs, for intelligent association control. This enables the new users to be attached to BSs with relatively low load in the long term, alleviating the problem of non-uniform user distribution and load imbalance across the network. Extensive simulations are performed with various user densities considering throughput fair and resource fair, as the resource allocation policies in each cell. It is observed that significant improvement in minimum throughput and fair user distribution is achieved by employing our proposed schemes, and preamble sequences can be effectively used as a leverage for better cell-site selection from the viewpoint of fairness provisioning. The load of the entire system is also observed to be balanced, which consequently enhances the capacity of the network, as evidenced by the simulation results.</p>

Association Control Based Load Balancing in Wireless Cellular Networks Using Preamble Sequences

<p>The efficient allocation and use of radio resources is crucial for achieving the maximum possible throughput and capacity in wireless networks. The conventional strongest signal-based user association in cellular networks generally considers only the strength of the signal while selecting a BS, and ignores the level of congestion or load at it. As a consequence, some BSs tend to suffer from heavy load, while their adjacent BSs may carry only light load. This load imbalance severely hampers the network from fully utilizing the network capacity and providing fair services to users. In this thesis, we investigate the applicability of the preamble code sequence, which is mainly used for cell identification, as an implicit information indicator for load balancing in cellular networks. By exploiting the high auto-correlation and low cross-correlation property among preamble sequences, we propose distributed load balancing schemes that implicitly obtain information about the load status of BSs, for intelligent association control. This enables the new users to be attached to BSs with relatively low load in the long term, alleviating the problem of non-uniform user distribution and load imbalance across the network. Extensive simulations are performed with various user densities considering throughput fair and resource fair, as the resource allocation policies in each cell. It is observed that significant improvement in minimum throughput and fair user distribution is achieved by employing our proposed schemes, and preamble sequences can be effectively used as a leverage for better cell-site selection from the viewpoint of fairness provisioning. The load of the entire system is also observed to be balanced, which consequently enhances the capacity of the network, as evidenced by the simulation results.</p>

Study and development of algorithms for managing and optimizing wireless resources in environments of multiple technologies

Λόγω των ριζικών αλλαγών στην καθημερινότητα μας, μια απότομη αύξηση της παγκόσμιας ασύρματης συνδεσιμότητας έχει παρατηρηθεί τα τελευταία χρόνια. Επομένως, τα παραδοσιακά δίκτυα μεγάλης εμβέλειας (macro-cells) είναι πλέον ανεπαρκή να εξυπηρετήσουν αποτελεσματικά τις απαιτήσεις των χρηστών τους. Αυτό οδήγησε στην παράλληλη ανάπτυξη μικρότερων και πυκνότερων ετερογενών κυψελών (Heterogeneous networks), η οποία προτείνεται ευρέως στο πλαίσιο των δικτύων 5ης γενιάς (5G). Επιπρόσθετα, εκεί εμφανίζονται οι έννοιες του «softwarization» και «cloudification», επιτρέποντας έτσι την εκμετάλλευση όλων των διαθέσιμων δικτυακών πόρων (radio resources) με ενιαίο τρόπο. Εκ πρώτης όψεως, τα παραπάνω φαντάζουν ιδανική λύση για το φαινόμενο έλλειψης πόρων (capacity crunch). Παρόλα αυτά, αρκετή προσοχή πρέπει να δοθεί, καθώς η πλειοψηφία των πυκνά τοποθετημένων ετερογενών κυψελών (ultra-dense HetNets) στα δίκτυα 5G περιέχει τεχνολογίες και πρότυπα που χρησιμοποιούν τις ίδιες περιορισμένες ζώνες συχνοτήτων. Εκτός αυτού, ελάχιστος έως καθόλου συντονισμός υπάρχει μεταξύ αυτών των προτύπων στα επίπεδα προτεραιότητας μεταδόσεων και συνύπαρξης. Επομένως, μεγάλη ποσότητα απρόβλεπτων παρεμβολών δημιουργείται, γεγονός που οδηγεί σε αμφισβητήσιμη απόδοση σε αυτά τα περιβάλλοντα. Τέλος, αφενός μεν ο χειρισμός των ασύρματων δικτυακών πόρων ως υπηρεσία (radio as a service) μπορεί να οδηγήσει σε πιο αποτελεσματική χρήση πόρων και σε σύγκριση με την στατική κατανομή φάσματος. Αφετέρου, αυτό αυξάνει κατά πολύ την πολυπλοκότητα όσον αφορά την ενορχήστρωση του δικτύου.Για να αντιμετωπιστεί αποτελεσματικά η έλλειψη φάσματος, απαιτείται προσεκτικός δικτυακός σχεδιασμός και ευέλικτη διαχείριση πόρων. Στόχος αυτής της διδακτορικής διατριβής είναι η ανάπτυξη και παρουσίαση νέων μοντέλων και μηχανισμών, τα οποία βελτιώνουν την αξιοποίηση των πόρων σε σύγχρονα ασύρματα συστήματα πολλαπλών προτύπων. Αρχικά, η παρούσα διατριβή, ασχολείται με τον εντοπισμό και την αποφυγή παρεμβολών στα ευρέως διαδεδομένα συστήματα IEEE 802.11 (Wi-Fi). Δεδομένου ότι το πρότυπο Wi-Fi κατέχει σημαντικό ρόλο στα δίκτυα 5G, η διατριβή αυτή παρουσιάζει αναλυτικά πως η ορθή φασματική ανάλυση μπορεί να ενισχύσει την απόδοση του δικτύου κάτω από σχήματα επιλογής σταθμού βάσης, επιλογής καναλιών και πρόβλεψης παρεμβολών στο μέλλον. Επιπρόσθετα, η διατριβή αυτή εστιάζει και στην δυναμική μίσθωση και τιμολόγηση των ασυρμάτων πόρων δικτύωσης σε περιβάλλοντα 5G. Για τον λόγο αυτό, δημιουργούνται τα προσχέδια για μια οντότητα που έχει ως σκοπό την δυναμική τιμολόγηση του διαθέσιμου φάσματος. Τέλος, αξίζει να σημειωθεί, ότι όλα τα μοντέλα και οι μηχανισμοί που αναπτύχθηκαν στο πλαίσιο αυτής της διατριβής έχουν αξιολογηθεί πειραματικά σε πραγματικές ασύρματες υποδομές (wireless testbeds).

A Survey: Nonorthogonal Multiple Access with Compressed Sensing Multiuser Detection for mMTC

One objective of the 5G communication system and beyond is to support massive machine type of communication (mMTC) to propel the fast growth of diverse Internet of Things use cases. The mMTC is aimed at providing connectivity to tens of billions of sensor nodes. The dramatic increase of sensor devices and massive connectivity impose critical challenges for the network to handle the enormous control signaling overhead with limited radio resources. Nonorthogonal multiple access (NOMA) is a new paradigm shift in the design of multiple user detection and multiple access. NOMA with compressive sensing-based multiuser detection is one of the promising candidates to address the challenges of mMTC. The survey article is aimed at providing an overview of the current state-of-art research work in various compressive sensing-based techniques that enable NOMA. We present characteristics of different algorithms and compare their pros and cons, thereby providing useful insights for researchers to make further contributions in NOMA using compressive sensing techniques. Nonorthogonal CDMA massive connectivity grant free medium access compressive sensing multiuser detection

Massive distributed IRS aided wireless communication with ON/OFF selection

The mobile communication system beyond fifth-generation (beyond 5G) is required to maintain higher transmission capacity and reliability than existing 5G systems. To meet these requirements, one promising solution is to incorporate an Intelligent Reflecting Surface (IRS). The IRS involves reconfiguring the wireless propagation environment and exploiting the radio resources, not only in the conventional frequency and time domains but also in the spatial domain by controlling the reflection amplitude and phase of the incident electromagnetic signal. However, increased deployment of IRSs brings about interference and greater complexity. Therefore, in this paper, we propose an ON/OFF IRS selection method on massive IRS aided wireless communications that can simultaneously achieve interference suppression and capacity improvement. In addition, the proposed method reduces operational complexity using a simple 1-bit control. The results of computer simulation and experiment show that the proposed method can improve the desired channel capacity beyond directly Single-Input Single-Output (SISO) communication without IRS while maintaining the interference level of an interfered receiver below a certain threshold.