Next generation Radio Access Networks (RANs) consider virtualized architectures in which base station functions are distributed in different logical nodes, connected through fronthaul (FH) links. To reduce the FH deployment costs and the required FH capacity, operators may install a single FH link shared among multiple cells and exploit key enabling techniques, such as modulation compression, to reduce FH data. In shared FH capacity scenarios, it is essential to provide efficient methods to control and optimize the FH resources’ utilization with limited impact on the air interface performance. In this paper, a multi-cell multi-user scenario with a shared FH link across multiple cells is considered. We focus on optimizing the resource allocation and modulation compression of each user, in a centralized and dynamic manner, aiming to maximize the air interface performance subject to a shared FH capacity constraint. The problem is formulated as a convex optimization problem, which allows deriving the optimal resource allocation and modulation compression per user. Then, we evaluate the proposed FH-aware scheduling methods against baseline holistic strategies over an end-to-end dynamic 5G NR system-level simulator based on ns-3. Under a tight available FH capacity, results show gains that vary from 16% to 567% in different percentile statistics of the user-perceived throughput.

Next generation Radio Access Networks (RANs) consider virtualized architectures in which base station functions are distributed in different logical nodes, connected through fronthaul (FH) links. To reduce the FH deployment costs and the required FH capacity, operators may install a single FH link shared among multiple cells and exploit key enabling techniques, such as modulation compression, to decrease the data rates over the FH. In shared FH capacity scenarios, it is essential to provide efficient methods to control and optimize the FH resources' utilization with limited impact on the air interface performance. In this paper, we propose and analyze different fronthaul-aware scheduling strategies, leveraging on modulation compression, for multi-cell multi-user scenarios with a shared FH link across multiple cells. We consider holistic approaches based on packet dropping at the PHY layer and postponing of MAC scheduling decisions, combined with the reduction of the modulation order per cell. Additionally, we propose optimization methods for resource allocation and dynamic modulation compression, in which the modulation order and resource block assignment is dynamically optimized per user and slot. We finally evaluate the proposed FH-aware scheduling methods over an end-to-end dynamic 5G NR system-level simulator based on ns-3.

Next generation Radio Access Networks (RANs) consider virtualized architectures in which base station functions are distributed in different logical nodes that are connected through fronthaul links. To reduce the required fronthaul capacity, modulation compression is considered as a key enabler. Modulation compression achieves fronthaul capacity reduction at the cost of reducing the maximum modulation order that can be used over the air interface, thus creating a cell-fronthaul trade-off. The trade-off is further accentuated and needs to be optimized appropriately when multiple cells share the same fronthaul link. In this paper, a multi-cell scenario with a shared fronthaul link across multiple cells is considered, and we focus on optimizing the modulation compression of each cell. We propose semi-static optimization procedures that aim at maximizing the air interface performance subject to a shared fronthaul capacity constraint, by taking into account the average traffic load and system configuration of every cell. The problem is formulated as a convex optimization problem, which allows deriving the optimal maximum modulation order that is permitted per cell, under two different optimization criteria. Then, we use a dynamic multi-cell 5G NR system-level simulator based on ns-3 to evaluate the proposed optimized solutions.

In today's cellular networks, an increasing number of connected devices on-board in fast-moving vehicles would require more efficient handover (HO) procedures. To this end, we investigate the utilization of mobile relay nodes (MRNs) in vehicles to facilitate efficient HO and HO-related power consumption reductions for all on-board user equipments (UEs). In particular, the potential gains in terms of HO rate, HO failure ratio (HOFR), ping-pong (PP) rate, and total power consumption are studied for different UE cluster sizes. To eliminate the measurement power-consuming procedure, uplink (UL) reference signals (RS) transmitted by UEs are exploited. Four different case scenarios are simulated utilizing both the DL and UL RS based HO procedure, with and without deploying MRNs on the buses traveling along the cell edges of surrounding macro BSs. Simulation results indicate that the UL RS based HO procedure can improve HO performance significantly because it reduces the air-interface signaling messages, namely the measurement report (MeasReport) transmission and reception. Also, in terms of power consumption, deploying MRNs is a more attractive solution with substantial power reduction for onboard UEs of higher cluster size.

Mobile relay node (MRN) is one of the cheaper options for reliable communication when users are moving by public transport (i.e. bus, tram, train, subway, etc.), especially in urban areas. Critically, MRNs need to maintain a backhaul connection with the fixed infrastructure via a donor eNB, (DeNB). If the MRN fails to successfully handover (HO) from one DeNB to another, it will create a single point of failure, i.e. the connection of all UEs connected to MRN will be dropped. In this paper, we address the HO performance of a MRN including a power consumption analysis thereof. We investigate the potential gains in terms of HO rate, HO failure ratio (HOFR), ping-pong (PP) rate and power consumption (both at UE and eNB) when a MRN is deployed on a bus traveling along the cell edges of surrounding macro BSs. We also look over the MRN HO failure cases to identify the causes of HO failures that are more critical for the UEs onboard. Numerical results indicate that deploying a MRN on the roof-top of a bus improves the HO rates 15%, HOFR 8%, PP rate 17%, UE power consumption 21%, and eNB power consumption 14% on average for all simulated cases. We have also established that UL transmission errors are the most dominant causes of turning MRN to a single point of failure during a HO.

In this paper, we address the signaling overhead and the power consumption that results from the transmission of handover-related signaling in a Long Term Evolution (LTE) cellular network. Specifically, we analyze the contribution of the different signaling messages over the air-interface, and their impact on power consumption both at the eNB and at the User Equipment (UE) during handover (HO). A quantitative analysis is provided using system level simulations. We observe that, within the HO process, the largest contributor to air-interface signaling overhead is the transmission of the measurement report by the UE. This uplink (UL) transmission suffers from different channel impairments, due to interference and transmission range, for particular cell sizes. As a consequence, uplink signaling retransmissions are triggered causing higher signaling load and consequently higher power consumption, this being especially detrimental to battery-powered devices.

This paper proposes an approach for providing 5G services to mobile users that is based on continuous ultra dense networks (C-UDNs). The proposed approach outperforms the widely accepted solution based on macro cells and massive MIMO systems (M-MIMO). In particular, we show that the performance of M-MIMO systems deployed on macro cells is significantly limited by channel aging. The proposed mobility solution based on uplink beacons overcomes the handover problem often linked to UDNs. Dense networks make it possible for users to transmit at a power lower than that of macro cells, thus making C-UDN more robust to pilot contamination and allowing for lower Channel State Information (CSI) latencies due to shorter reuse distance of UL pilots. Extensive numerical results from detailed systemlevel simulations are provided in order to compare and highlight the benefits of the proposed C-UDN mobility solution to that of a macro M-MIMO deployment.

This paper proposes a novel user-transparent mobility concept based on the transmission of uplink reference signals (beacons) using Zadoff-Chu signature sequences. Unlike legacy mobility schemes, the proposed scheme overcomes the need for the user to perform time and energy consuming downlink measurements and reporting them back to the network. This is particularly relevant for ultra dense network (UDN) deployments and high user densities as forecasted in the near future. The system requirements to support uplink beacons are presented and a detailed design for the signature sequence is provided to support a variety of system configurations and deployment cases. Numerical results illustrate the suitability and sufficiency of beacon resources as well as the reliability of the proposed beacon design in order to support a truly user-transparent and border-less mobility concept.

The Cognitive Radio (CR) paradigm provides mechanisms and methodologies for an utmost and efficient use of scarce spectrum resources. Among its implementations, Opportunistic Spectrum Access (OSA) enables the use of otherwise-unutilized licensed spectrum provided no interference is caused to the licensee. This paper focuses on the application of this concept for indoor femtocell deployments where, in addition to own licensed spectrum resources, opportunistic spectrum resources can be aggregated. Provided certain interference among femtocells, coordination mechanisms are required. In this framework, this paper studies the use of Media Independent Handover (MIH) signaling to report interference measurements that allow a central controller to make femtocells share white spaces. Moreover, whenever an excessive femto-to-femto interference would require coordination, the proposed opportunistic spectrum access scheme enhances spectrum efficiency and reduces interferences. Results indicate that the proposed opportunistic system significantly improves capacity without requiring additional intelligence in the femtocell.

The Self Organizing Network (SON) concept is a promising paradigm aiming to reduce both the capital and operational expenditures (CAPEX/OPEX) in future wireless networks through efficient self-configuration, self-optimization and self-healing functionalities. As for self-optimization, much effort has been devoted to standalone SON control loops, which, upon network metric observation, dynamically adjust the appropriate network parameters to enhance the overall network performance. However, less explored simultaneous operation of several SON control loops may cause conflicts between parameter adjustment and/or metric performance outcome. This paper focuses on SON mechanism interactions, providing a framework for further understanding and analysis. A basic two-SON mechanism interaction scenario will be provided along with an initial assessment of a simple SON interaction control.

In this letter a Discrete-Time Markov Chain (DTMC) framework is adopted to capture the effect of flexible spectrum channelization for the opportunistic access of secondary users (SUs) in a primary-secondary shared spectrum scenario. Two implementation alternatives are proposed: a fixed channelization scheme (FCS) and an adaptive channelization scheme (ACS). Moreover, service-type characterization of SUs is also addressed by defining time vs. volume based services. Results indicate the suitability of the ACS over the FCS.

Spectrum sensing is one key enabler towards opportunistic spectrum access in cognitive radio networks. Such scenarios allow cognitive users (a.k.a. secondary users) to access some licensed spectrum band as long as they do not interfere with the licensed (or primary) users. The main goal is to achieve an efficient and utmost access to the otherwise underutilized spectrum resources while still guaranteeing primary users a non-harmful operation. Spectrum sensing can be then used by secondary users to detect spectrum holes that may be accessed in a non-interfering manner. However, spectrum sensing may be subject to errors in the form of false-alarm and misdetection. False-alarm causes spectrum under-use while misdetection leads to spectrum interference between primary and secondary users. Unfortunately, these two magnitudes pose a trade-off on the sensing mechanism: low misdetection is achieved at the expense of high false alarm and vice versa. Consequently, an adequate operating point of the sensing mechanism should be determined. In this work we evaluate the impact of false-alarm and misdetection errors on the performance of a spectrum sensing scenario. We use a discrete time Markov chain (DTMC) model and we determine the suitable operating point for the sensing mechanism under different traffic load conditions such that some quality of service is attained by both primary and secondary users. Performance results reveal that by effectively choosing the operation point bearing in mind the traffic load levels will lead to enhanced perceived quality of service of both primary and secondary users.

This work takes as a reference the scenario of heterogeneous radio access networks where several radio access technologies (RATs) coexist and cooperate providing a range of services over a specific coverage area. In this context, an appropriate RAT must be selected upon each user request in order to provide the specified quality of service (QoS) level for the requested service. Despite of having an efficient RAT selection mechanism, the intrinsic network dynamics may pose some risk on the QoS guarantees in each RAT which may not be met thus leading to a degraded network performance. In such situations, the network undergoes so-called radio access congestion situations. In this work, a statistical characterization of radio access congestion is provided for TDMA and WCDMA based systems. Furthermore, the impact of several representative RAT selection policies is evaluated in terms of their obtained congestion probability. Numerical results conclude that a proper knowledge of congestion information can be used as a relevant input for RAT selection specification.

An efficient and utmost utilization of radio spectrum resources has stimulated the introduction of what has been termed dynamic spectrum access methodologies and implementations. While the traditional approach has been based on licensed (or primary) spectrum access, this new communication paradigm enables an opportunistic secondary access to shared spectrum resources provided mutual interference is kept below predefined margins. In this paper we propose a novel and flexible framework so as to account for primary-secondary spectrum sharing scenarios. In this sense, the use of a discrete time Markov chain (DTMC) model is suggested and further justified. Some illustrative results are provided and validated against a system-level simulator thus confirming the suitability of the proposed approach.

This paper addresses the problem of Radio Access Technology (RAT) selection in heterogeneous multi-access/multi-service scenarios. For such purpose, a Markov model is proposed to compare the performance of various RAT selection policies within these scenarios. The novelty of the approach resides in the embedded definition of the aforementioned RAT selection policies within the Markov chain. In addition, the model also considers the constraints imposed by those users with terminals that only support a subset of all the available RATs (i.e. multi-mode terminal capabilities). Furthermore, several performance metrics may be measured to evaluate the behaviour of the proposed RAT selection policies under varying offered traffic conditions. In order to illustrate the validation and suitability of the proposed model, some examples of operative radio access networks are provided, including the GSM/EDGE Radio Access Network (GERAN) and the UMTS Radio Access Network (UTRAN), as well as several service-based, load-balancing and terminal-driven RAT selection strategies. The flexibility exhibited by the presented model enables to extend these RAT selection policies to others responding to diverse criteria. The model is successfully validated by means of comparing the Markov model results with those of system-level simulations.

Among the common radio resource management (CRRM) functions that are responsible for the proper allocation of resources in a multi-access network, congestion control is the one devoted to overcome potential QoS failures due to the inherent dynamics of the network. In this paper we address the problem of congestion control in a scenario considering the GSM/EDGE radio access network (GERAN) and the UMTS terrestrial radio access network (UTRAN). In particular, we face the problem where the two available radio access technologies (RATs) undergo simultaneous congestion situations. For this case, a congestion resolution scheme based on vertical (inter-system) handover (VHO) jointly with a bit-rate reduction (BRR) scheme is proposed and evaluated for a mixed services scenario considering voice and data users.

In order to support the conceptual development of common radio resource management (CRRM) algorithms, this paper provides an analytical approach to the performance evaluation of Radio Access Technology (RAT) selection procedures in a multi-RAT/multiservice environment. In particular, a 4-Dimensional (4D) Markovian model is devised so as to consider the allocation of voice and data services in a GERAN/UTRAN system. Through the analytical definition of well-established Key Performance Indicators (KPIs) we provide numerical results on the evaluation of a load balancing RAT allocation policy.