225 research outputs found
Fast and efficient energy-oriented cell assignment in heterogeneous networks
The cell assignment problem is combinatorial, with increased complexity when it is tackled considering resource allocation. This paper models joint cell assignment and resource allocation for cellular heterogeneous networks, and formalizes cell assignment as an optimization problem. Exact algorithms can find optimal solutions to the cell assignment problem, but their execution time increases drastically with realistic network deployments. In turn, heuristics are able to find solutions in reasonable execution times, but they get usually stuck in local optima, thus failing to find optimal solutions. Metaheuristic approaches have been successful in finding solutions closer to the optimum one to combinatorial problems for large instances. In this paper we propose a fast and efficient heuristic that yields very competitive cell assignment solutions compared to those obtained with three of the most widely-used metaheuristics, which are known to find solutions close to the optimum due to the nature of their search space exploration. Our heuristic approach adds energy expenditure reduction in its algorithmic design. Through simulation and formal statistical analysis, the proposed scheme has been proved to produce efficient assignments in terms of the number of served users, resource allocation and energy savings, while being an order of magnitude faster than metaheuritsic-based approaches.This paper has been supported by the National Council of Research and Technology (CONACYT) through Grant FONCICYT/272278 and the ERANetLAC (Network of the European Union, Latin America, and the Caribbean Countries) Project ELAC2015/T100761. This paper is partially supported also by the ADVICE Project, TEC2015-71329 (MINECO/FEDER) and the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No 777067 (NECOS Project)
A Genetic Algorithm-based Beamforming Approach for Delay-constrained Networks
In this paper, we study the performance of initial access beamforming schemes
in the cases with large but finite number of transmit antennas and users.
Particularly, we develop an efficient beamforming scheme using genetic
algorithms. Moreover, taking the millimeter wave communication characteristics
and different metrics into account, we investigate the effect of various
parameters such as number of antennas/receivers, beamforming resolution as well
as hardware impairments on the system performance. As shown, our proposed
algorithm is generic in the sense that it can be effectively applied with
different channel models, metrics and beamforming methods. Also, our results
indicate that the proposed scheme can reach (almost) the same end-to-end
throughput as the exhaustive search-based optimal approach with considerably
less implementation complexity
Open Cell-less Network Architecture and Radio Resource Management for Future Wireless Communication Systems
In recent times, the immense growth of wireless traffic data generated from massive mobile
devices, services, and applications results in an ever-increasing demand for huge
bandwidth and very low latency, with the future networks going in the direction of achieving
extreme system capacity and ultra reliable low latency communication (URLLC). Several
consortia comprising major international mobile operators, infrastructure manufacturers,
and academic institutions are working to develop and evolve the current generation
of wireless communication systems, i.e., fifth generation (5G) towards a sixth generation
(6G) to support improved data rates, reliability, and latency. Existing 5G networks are
facing the latency challenges in a high-density and high-load scenario for an URLLC network
which may coexist with enhanced mobile broadband (eMBB) services. At the same
time, the evolution of mobile communications faces the important challenge of increased
network power consumption. Thus, energy efficient solutions are expected to be deployed
in the network in order to reduce power consumption while fulfilling user demands for
various user densities. Moreover, the network architecture should be dynamic according
to the new use cases and applications. Also, there are network migration challenges for
the multi-architecture coexistence networks.
Recently, the open radio access network (O-RAN) alliance was formed to evolve
RANs with its core principles being intelligence and openness. It aims to drive the mobile
industry towards an ecosystem of innovative, multi-vendor, interoperable, and autonomous
RAN, with reduced cost, improved performance and greater agility. However,
this is not standardized yet and still lacks interoperability. On the other hand, the cell-less
radio access network (RAN) was introduced to boost the system performance required for
the new services. However, the concept of cell-less RAN is still under consideration from
the deployment point of view with the legacy cellular networks. The virtualization, centralization and cooperative communication which enables the cell-less RAN can further
benefit from O-RAN based architecture.
This thesis addresses the research challenges facing 5G and beyond networks towards
6G networks in regard to new architectures, spectral efficiency, latency, and energy efficiency.
Different system models are stated according to the problem and several solution
schemes are proposed and developed to overcome these challenges. This thesis
contributes as follows. Firstly, the cell-less technology is proposed to be implemented
through an Open RAN architecture, which could be supervised with the near real-time
RAN intelligent controller (near-RT-RIC). The cooperation is enabled for intelligent and
smart resource allocation for the entire RAN. Secondly, an efficient radio resource optimization
mechanism is proposed for the cell-less architecture to improve the system
capacity of the future 6G networks. Thirdly, an optimized and novel resource scheduling
scheme is presented that reduces latency for the URLLC users in an efficient resource
utilization manner to support scenarios with high user density. At the same time, this radio
resource management (RRM) scheme, while minimizing the latency, also overcomes
another important challenge of eMBB users, namely the throughput of those who coexist
in such a highly loaded scenario with URLLC users. Fourthly, a novel energy-efficiency
enhancement scheme, i.e., (3 × E) is designed to increase the transmission rate per energy
unit, with stable performance within the cell-less RAN architecture. Our proposed
(3 × E) scheme activates two-step sleep modes (i.e., certain phase and conditional phase)
through the intelligent interference management for temporarily switching access points
(APs) to sleep, optimizing the network energy efficiency (EE) in highly loaded scenarios,
as well as in scenarios with lower load. Finally, a multi-architecture coexistence (MACO)
network model is proposed to enable inter-connection of different architectures through
coexistence and cooperation logical switches in order to enable smooth deployment of a
cell-less architecture within the legacy networks.
The research presented in this thesis therefore contributes new knowledge in the cellless
RAN architecture domain of the future generation wireless networks and makes important
contributions to this field by investigating different system models and proposing
solutions to significant issues.Programa de Doctorado en Multimedia y Comunicaciones por la Universidad Carlos III de Madrid y la Universidad Rey Juan CarlosPresidenta: Matilde Pilar Sánchez Fernández.- Secretario: Alberto Álvarez Polegre.- Vocal: José Francisco Monserrat del Rí
Cooperative Transmission for Downlink Distributed Antenna in Time Division Duplex System
Multi-user distributed antenna system (MU-DAS) systems play the
essential role in improving throughput performance in wireless communications. This improvement can be achieved by exploiting the spatial
domain and without the need of additional power and bandwidth. In
this thesis, three main issues which are of importance to the data rate
transmission have been investigated.
Firstly, user clustering in MU-DAS downlink systems has been considered, where this technique can be effciently used to reduce the complexity and cost caused by radio frequency chains, associated with antennas while keeping most of the diversity advantages of the system.
The proposed user clustering algorithm which can select an optimal set
of antennas for transmission. The capacity achieved by the proposed
algorithm is almost same as the capacity of the optimum search method,
with much lower complexity.
Secondly, interference alignment in MU-DAS downlink systems has
been studied. The inter-cluster interference is uncoordinated and limits
the system performance. The inter-cluster interference should be eliminated or minimized carefully. The interference alignment is proposed to
consolidate the strong inter-cluster interference into smaller dimensions
of signal space at each user and use the remaining dimensions to transmit
the desired signals without any interference. The performance of single
cluster is better than the proposed algorithm due to the absence of intercluster interference in the single cluster. The numerical shows that the
proposed algorithm is more suitable in multi-cell DAS environment due
to the presence of inter-cell interference.
Finally, the impact of different user mobility on TDD downlink MUDAS has been studied. The downlink data transmission in time division
duplex (TDD) systems is optimized according to the channel state information (CSI) which is obtained at the uplink time slot. However, the
actual channel at downlink time slot may be different from the estimated
channel due to channel variation in mobility environment. Based on mobility state information (MSI), an autocorrelation based feedback interval
adjustment technique is proposed. The proposed technique adjusts the
CSI update interval and mitigates the performance degradation imposed
by the user mobility and the transmission delay. Cooperative clusters are
formed to maximize sum rate. In order to reduce the computational complexity, a channel gain based antenna selection and signal-to-interference
plus noise ratio (SINR) based user clustering are developed. A downlink
ergodic capacity is derived in single user clustering. The derived analytical expressions of the downlink ergodic capacity are verified by system
simulations. Numerical results show that the proposed scheme can improved sum rate over the non cooperative system and no MSI knowledge.
The proposed technique has good performance for a wide range of user
speed and suitable for future wireless communications systems
The electronically steerable parasitic array radiator antenna for wireless communications : signal processing and emerging techniques
Smart antenna technology is expected to play an important role in future wireless
communication networks in order to use the spectrum efficiently, improve the
quality of service, reduce the costs of establishing new wireless paradigms and
reduce the energy consumption in wireless networks. Generally, smart antennas
exploit multiple widely spaced active elements, which are connected to separate
radio frequency (RF) chains. Therefore, they are only applicable to base stations
(BSs) and access points, by contrast with modern compact wireless terminals with
constraints on size, power and complexity. This dissertation considers an alternative
smart antenna system the electronically steerable parasitic array radiator
(ESPAR) which uses only a single RF chain, coupled with multiple parasitic elements.
The ESPAR antenna is of significant interest because of its
flexibility in beamforming by tuning a number of easy-to-implement reactance loads connected
to parasitic elements; however, parasitic elements require no expensive RF circuits.
This work concentrates on the study of the ESPAR antenna for compact
transceivers in order to achieve some emerging techniques in wireless communications.
The work begins by presenting the work principle and modeling of the ESPAR
antenna and describes the reactance-domain signal processing that is suited to the
single active antenna array, which are fundamental factors throughout this thesis.
The major contribution in this chapter is the adaptive beamforming method
based on the ESPAR antenna. In order to achieve fast convergent beamforming
for the ESPAR antenna, a modified minimum variance distortionless response
(MVDR) beamfomer is proposed. With reactance-domain signal processing, the
ESPAR array obtains a correlation matrix of receive signals as the input to the
MVDR optimization problem. To design a set of feasible reactance loads for a desired
beampattern, the MVDR optimization problem is reformulated as a convex
optimization problem constraining an optimized weight vector close to a feasible
solution. Finally, the necessary reactance loads are optimized by iterating the convex problem and a simple projector. In addition, the generic algorithm-based
beamforming method has also studied for the ESPAR antenna.
Blind interference alignment (BIA) is a promising technique for providing an optimal
degree of freedom in a multi-user, multiple-inputsingle-output broadcast
channel, without the requirements of channel state information at the transmitters.
Its key is antenna mode switching at the receive antenna. The ESPAR
antenna is able to provide a practical solution to beampattern switching (one
kind of antenna mode switching) for the implementation of BIA. In this chapter,
three beamforming methods are proposed for providing the required number of
beampatterns that are exploited across one super symbol for creating the channel
fluctuation patterns seen by receivers. These manually created channel
fluctuation
patterns are jointly combined with the designed spacetime precoding in order to
align the inter-user interference. Furthermore, the directional beampatterns designed
in the ESPAR antenna are demonstrated to improve the performance of
BIA by alleviating the noise amplification.
The ESPAR antenna is studied as the solution to interference mitigation in small
cell networks. Specifically, ESPARs analog beamforming presented in the previous
chapter is exploited to suppress inter-cell interference for the system scenario,
scheduling only one user to be served by each small BS at a single time. In
addition, the ESPAR-based BIA is employed to mitigate both inter-cell and intracell
interference for the system scenario, scheduling a small number of users to be
simultaneously served by each small BS for a single time.
In the cognitive radio (CR) paradigm, the ESPAR antenna is employed for spatial
spectrum sensing in order to utilize the new angle dimension in the spectrum
space besides the conventional frequency, time and space dimensions. The twostage
spatial spectrum sensing method is proposed based on the ESPAR antenna
being targeted at identifying white spectrum space, including the new angle dimension.
At the first stage, the occupancy of a specific frequency band is detected
by conventional spectrum-sensing methods, including energy detector and
eigenvalue-based methods implemented with the switched-beam ESPAR antenna. With the presence of primary users, their directions are estimated at the second
stage, by high-resolution angle-of-arrival (AoA) estimation algorithms. Specifically, the compressive sensing technology has been studied for AoA detection with
the ESPAR antenna, which is demonstrated to provide high-resolution estimation
results and even to outperform the reactance-domain multiple signal classification
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