357 research outputs found
Weighted Sum Rate Maximization for Downlink OFDMA with Subcarrier-pair based Opportunistic DF Relaying
This paper addresses a weighted sum rate (WSR) maximization problem for
downlink OFDMA aided by a decode-and-forward (DF) relay under a total power
constraint. A novel subcarrier-pair based opportunistic DF relaying protocol is
proposed. Specifically, user message bits are transmitted in two time slots. A
subcarrier in the first slot can be paired with a subcarrier in the second slot
for the DF relay-aided transmission to a user. In particular, the source and
the relay can transmit simultaneously to implement beamforming at the
subcarrier in the second slot. Each unpaired subcarrier in either the first or
second slot is used for the source's direct transmission to a user. A benchmark
protocol, same as the proposed one except that the transmit beamforming is not
used for the relay-aided transmission, is also considered. For each protocol, a
polynomial-complexity algorithm is developed to find at least an approximately
optimum resource allocation (RA), by using continuous relaxation, the dual
method, and Hungarian algorithm. Instrumental to the algorithm design is an
elegant definition of optimization variables, motivated by the idea of
regarding the unpaired subcarriers as virtual subcarrier pairs in the direct
transmission mode. The effectiveness of the RA algorithm and the impact of
relay position and total power on the protocols' performance are illustrated by
numerical experiments. The proposed protocol always leads to a maximum WSR
equal to or greater than that for the benchmark one, and the performance gain
of using the proposed one is significant especially when the relay is in close
proximity to the source and the total power is low. Theoretical analysis is
presented to interpret these observations.Comment: 8 figures, accepted and to be published in IEEE Transactions on
Signal Processing. arXiv admin note: text overlap with arXiv:1301.293
Resource Management in Multicarrier Based Cognitive Radio Systems
The ever-increasing growth of the wireless application and services affirms the importance of the effective usage of the limited radio spectrum. Existing spectrum management policies have led to significant spectrum under-utilization. Recent measurements showed that large range of the spectrum is sparsely used in both temporal and spatial manner. This conflict
between the inefficient usage of the spectrum and the continuous evolution in the wireless communication calls upon the development of more flexible management policies. Cognitive radio (CR) with the dynamic spectrum access (DSA) is considered to be a key technology in making the best solution of this conflict by allowing a group of secondary users (SUs) to share the radio spectrum originally allocated to the primary user (PUs). The operation of CR should not negatively alter the performance of the PUs. Therefore, the interference control along with the highly dynamic nature of PUs activities open up new resource allocation problems in CR systems. The resource allocation algorithms should ensure an effective share of the temporarily available frequency bands and deliver the solutions in timely fashion to cope with quick changes in the network.
In this dissertation, the resource management problem in multicarrier based CR systems is considered. The dissertation focuses on three main issues: 1) design of efficient resource allocation algorithms to allocate subcarriers and powers between SUs such that no harmful interference is introduced to PUs, 2) compare the spectral efficiency of using different multicarrier schemes in the CR physical layer, specifically, orthogonal frequency division multiplexing (OFDM) and filter bank multicarrier (FBMC) schemes, 3) investigate the impact of the different constraints values on the overall performance of the CR system.
Three different scenarios are considered in this dissertation, namely downlink transmission, uplink transmission, and relayed transmission. For every scenario, the optimal solution is examined and efficient sub-optimal algorithms are proposed to reduce the computational burden of obtaining the optimal solution. The suboptimal algorithms are developed by separate the subcarrier and power allocation into two steps in downlink and uplink scenarios. In the relayed scenario, dual decomposition technique is used to obtain an asymptotically optimal solution, and a joint heuristic algorithm is proposed to find the suboptimal solution. Numerical simulations show that the proposed suboptimal algorithms achieve a near optimal performance and perform better than the existing algorithms designed for cognitive and non-cognitive systems. Eventually, the ability of FBMC to overcome the OFDM drawbacks and achieve more spectral efficiency is verified which recommends the consideration of FBMC in the future CR systems.El crecimiento continuo de las aplicaciones y servicios en sistemas inal´ambricos, indica la
importancia y necesidad de una utilizaci´on eficaz del espectro radio. Las pol´ıticas actuales de
gesti´on del espectro han conducido a una infrautilizaci´on del propio espectro radioel´ectrico.
Recientes mediciones en diferentes entornos han mostrado que gran parte del espectro queda
poco utilizado en sus ambas vertientes, la temporal, y la espacial. El permanente conflicto
entre el uso ineficiente del espectro y la evoluci´on continua de los sistemas de comunicaci´on
inal´ambrica, hace que sea urgente y necesario el desarrollo de esquemas de gesti´on del espectro
m´as flexibles.
Se considera el acceso din´amico (DSA) al espectro en los sistemas cognitivos como una
tecnolog´ıa clave para resolver este conflicto al permitir que un grupo de usuarios secundarios
(SUs) puedan compartir y acceder al espectro asignado inicialmente a uno o varios usuarios
primarios (PUs). Las operaciones de comunicaci´on llevadas a cabo por los sistemas radio
cognitivos no deben en ning´un caso alterar (interferir) los sistemas primarios. Por tanto, el
control de la interferencia junto al gran dinamismo de los sistemas primarios implica nuevos
retos en el control y asignaci´on de los recursos radio en los sistemas de comunicaci´on CR. Los
algoritmos de gesti´on y asignaci´on de recursos (Radio Resource Management-RRM) deben
garantizar una participaci´on efectiva de las bandas con frecuencias disponibles temporalmente,
y ofrecer en cada momento oportunas soluciones para hacer frente a los distintos cambios
r´apidos que influyen en la misma red.
En esta tesis doctoral, se analiza el problema de la gesti´on de los recursos radio en sistemas
multiportadoras CR, proponiendo varias soluciones para su uso eficaz y coexistencia con los
PUs. La tesis en s´ı, se centra en tres l´ıneas principales: 1) el dise˜no de algoritmos eficientes de gesti´on de recursos para la asignaci´on de sub-portadoras y distribuci´on de la potencia en
sistemas segundarios, evitando asi cualquier interferencia que pueda ser perjudicial para el
funcionamiento normal de los usuarios de la red primaria, 2) analizar y comparar la eficiencia
espectral alcanzada a la hora de utilizar diferentes esquema de transmisi´on multiportadora en
la capa f´ısica del sistema CR, espec´ıficamente en sistemas basados en OFDM y los basados en
banco de filtros multiportadoras (Filter bank Multicarrier-FBMC), 3) investigar el impacto de
las diferentes limitaciones en el rendimiento total del sistema de CR.
Los escenarios considerados en esta tesis son tres, es decir; modo de transmisi´on
descendente (downlink), modo de transmisi´on ascendente (uplink), y el modo de transmisi´on
”Relay”. En cada escenario, la soluci´on ´optima es examinada y comparada con algoritmos sub-
´optimos que tienen como objetivo principal reducir la carga computacional. Los algoritmos
sub-´optimos son llevados a cabo en dos fases mediante la separaci´on del propio proceso de
distribuci´on de subportadoras y la asignaci´on de la potencia en los modos de comunicaci´on
descendente (downlink), y ascendente (uplink). Para los entornos de tipo ”Relay”, se ha
utilizado la t´ecnica de doble descomposici´on (dual decomposition) para obtener una soluci´on
asint´oticamente ´optima. Adem´as, se ha desarrollado un algoritmo heur´ıstico para poder obtener
la soluci´on ´optima con un reducido coste computacional.
Los resultados obtenidos mediante simulaciones num´ericas muestran que los algoritmos
sub-´optimos desarrollados logran acercarse a la soluci´on ´optima en cada uno de los entornos
analizados, logrando as´ı un mayor rendimiento que los ya existentes y utilizados tanto en
entornos cognitivos como no-cognitivos. Se puede comprobar en varios resultados obtenidos
en la tesis la superioridad del esquema multiportadora FBMC sobre los sistemas basados en
OFDM para los entornos cognitivos, causando una menor interferencia que el OFDM en
los sistemas primarios, y logrando una mayor eficiencia espectral. Finalmente, en base a lo
analizado en esta tesis, podemos recomendar al esquema multiportadora FBMC como una
id´onea y potente forma de comunicaci´on para las futuras redes cognitivas
Resource Allocation for Secure Gaussian Parallel Relay Channels with Finite-Length Coding and Discrete Constellations
We investigate the transmission of a secret message from Alice to Bob in the
presence of an eavesdropper (Eve) and many of decode-and-forward relay nodes.
Each link comprises a set of parallel channels, modeling for example an
orthogonal frequency division multiplexing transmission. We consider the impact
of discrete constellations and finite-length coding, defining an achievable
secrecy rate under a constraint on the equivocation rate at Eve. Then we
propose a power and channel allocation algorithm that maximizes the achievable
secrecy rate by resorting to two coupled Gale-Shapley algorithms for stable
matching problem. We consider the scenarios of both full and partial channel
state information at Alice. In the latter case, we only guarantee an outage
secrecy rate, i.e., the rate of a message that remains secret with a given
probability. Numerical results are provided for Rayleigh fading channels in
terms of average outage secrecy rate, showing that practical schemes achieve a
performance quite close to that of ideal ones
Power Allocation for Adaptive OFDM Index Modulation in Cooperative Networks
In this paper, we propose a power allocation strategy for the adaptive
orthogonal frequency-division multiplexing (OFDM) index modulation (IM) in
cooperative networks. The allocation strategy is based on the
Karush-Kuhn-Tucker (KKT) conditions, and aims at maximizing the average network
capacity according to the instantaneous channel state information (CSI). As the
transmit power at source and relay is constrained separately, we can thus
formulate an optimization problem by allocating power to active subcarriers.
Compared to the conventional uniform power allocation strategy, the proposed
dynamic strategy can lead to a higher average network capacity, especially in
the low signal-to-noise ratio (SNR) region. The analysis is also verified by
numerical results produced by Monte Carlo simulations. By applying the proposed
power allocation strategy, the efficiency of adaptive OFDM IM can be enhanced
in practice, which paves the way for its implementation in the future,
especially for cell-edge communications
Linear Precoding Designs for Amplify-and-Forward Multiuser Two-Way Relay Systems
Two-way relaying can improve spectral efficiency in two-user cooperative
communications. It also has great potential in multiuser systems. A major
problem of designing a multiuser two-way relay system (MU-TWRS) is transceiver
or precoding design to suppress co-channel interference. This paper aims to
study linear precoding designs for a cellular MU-TWRS where a multi-antenna
base station (BS) conducts bi-directional communications with multiple mobile
stations (MSs) via a multi-antenna relay station (RS) with amplify-and-forward
relay strategy. The design goal is to optimize uplink performance, including
total mean-square error (Total-MSE) and sum rate, while maintaining individual
signal-to-interference-plus-noise ratio (SINR) requirement for downlink
signals. We show that the BS precoding design with the RS precoder fixed can be
converted to a standard second order cone programming (SOCP) and the optimal
solution is obtained efficiently. The RS precoding design with the BS precoder
fixed, on the other hand, is non-convex and we present an iterative algorithm
to find a local optimal solution. Then, the joint BS-RS precoding is obtained
by solving the BS precoding and the RS precoding alternately. Comprehensive
simulation is conducted to demonstrate the effectiveness of the proposed
precoding designs.Comment: 13 pages, 12 figures, Accepted by IEEE TW
A Framework for Enhancing the Energy Efficiency of IoT Devices in 5G Network
A wide range of services, such as improved mobile broadband, extensive machine-type communication, ultra-reliability, and low latency, are anticipated to be delivered via the 5G network. The 5G network has developed as a multi-layer network that uses numerous technological advancements to provide a wide array of wireless services to fulfil such a diversified set of requirements. Several technologies, including software-defined networking, network function virtualization, edge computing, cloud computing, and tiny cells, are being integrated into the 5G networks to meet the needs of various requirements. Due to the higher power consumption that will arise from such a complicated network design, energy efficiency becomes crucial. The network machine learning technique has attracted a lot of interest from the scientific community because it has the potential to play a crucial role in helping to achieve energy efficiency. Utilization factor, access latency, arrival rate, and other metrics are used to study the proposed scheme. It is determined that our system outperforms the present scheme after comparing the suggested scheme to these parameters
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