800 research outputs found
Exploiting Multi-Antennas for Opportunistic Spectrum Sharing in Cognitive Radio Networks
In cognitive radio (CR) networks, there are scenarios where the secondary
(lower priority) users intend to communicate with each other by
opportunistically utilizing the transmit spectrum originally allocated to the
existing primary (higher priority) users. For such a scenario, a secondary user
usually has to trade off between two conflicting goals at the same time: one is
to maximize its own transmit throughput; and the other is to minimize the
amount of interference it produces at each primary receiver. In this paper, we
study this fundamental tradeoff from an information-theoretic perspective by
characterizing the secondary user's channel capacity under both its own
transmit-power constraint as well as a set of interference-power constraints
each imposed at one of the primary receivers. In particular, this paper
exploits multi-antennas at the secondary transmitter to effectively balance
between spatial multiplexing for the secondary transmission and interference
avoidance at the primary receivers. Convex optimization techniques are used to
design algorithms for the optimal secondary transmit spatial spectrum that
achieves the capacity of the secondary transmission. Suboptimal solutions for
ease of implementation are also presented and their performances are compared
with the optimal solution. Furthermore, algorithms developed for the
single-channel transmission are also extended to the case of multi-channel
transmission whereby the secondary user is able to achieve opportunistic
spectrum sharing via transmit adaptations not only in space, but in time and
frequency domains as well.Comment: Extension of IEEE PIMRC 2007. 35 pages, 6 figures. Submitted to IEEE
Journal of Special Topics in Signal Processing, special issue on Signal
Processing and Networking for Dynamic Spectrum Acces
Mathematical optimization techniques for resource allocation and spatial multiplexing in spectrum sharing networks
Due to introduction of smart phones with data intensive multimedia and interactive applications and exponential growth of wireless devices, there is a shortage for useful radio spectrum. Even though the spectrum has become crowded, many spectrum occupancy measurements indicate that most of the allocated spectrum is underutilised. Hence radically new approaches in terms of allocation of wireless resources are required for better utilization of radio spectrum.
This has motivated the concept of opportunistic spectrum sharing or
the so-called cognitive radio technology that has great potential to improve spectrum utilization. The cognitive radio technology allows an opportunistic
user namely the secondary user to access the spectrum of the licensed user (known as primary user) provided that the secondary transmission does not harmfully affect the primary user. This is possible with the introduction
of advanced resource allocation techniques together with the use of wireless relays and spatial diversity techniques.
In this thesis, various mathematical optimization techniques have been developed for the efficient use of radio spectrum within the context of spectrum sharing networks. In particular, optimal power allocation techniques and centralised and distributed beamforming techniques have been developed. Initially, an optimization technique for subcarrier and power allocation
has been proposed for an Orthogonal Frequency Division Multiple Access (OFDMA) based secondary wireless network in the presence of multiple primary users. The solution is based on integer linear programming with
multiple interference leakage and transmission power constraints. In order to enhance the spectrum efficiency further, the work has been extended to allow multiple secondary users to occupy the same frequency band under a multiple-input and multiple-output (MIMO) framework. A sum rate maximization technique based on uplink-downlink duality and dirty paper coding has been developed for the MIMO based OFDMA network. The work has
also been extended to handle fading scenarios based on maximization of ergodic capacity. The optimization techniques for MIMO network has been extended to a spectrum sharing network with relays. This has the advantage
of extending the coverage of the secondary network and assisting the primary network in return for the use of the primary spectrum. Finally, instead of considering interference mitigation, the recently emerged concept of
interference alignment has been used for the resource allocation in spectrum sharing networks. The performances of all these new algorithms have been demonstrated using MATLAB based simulation studies
Dynamic Resource Allocation in Cognitive Radio Networks: A Convex Optimization Perspective
This article provides an overview of the state-of-art results on
communication resource allocation over space, time, and frequency for emerging
cognitive radio (CR) wireless networks. Focusing on the
interference-power/interference-temperature (IT) constraint approach for CRs to
protect primary radio transmissions, many new and challenging problems
regarding the design of CR systems are formulated, and some of the
corresponding solutions are shown to be obtainable by restructuring some
classic results known for traditional (non-CR) wireless networks. It is
demonstrated that convex optimization plays an essential role in solving these
problems, in a both rigorous and efficient way. Promising research directions
on interference management for CR and other related multiuser communication
systems are discussed.Comment: to appear in IEEE Signal Processing Magazine, special issue on convex
optimization for signal processin
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
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
Resource allocation for transmit hybrid beamforming in decoupled millimeter wave multiuser-MIMO downlink
This paper presents a study on joint radio resource allocation and hybrid precoding in multicarrier massive multiple-input multiple-output communications for 5G cellular networks. In this paper, we present the resource allocation algorithm to maximize the proportional fairness (PF) spectral efficiency under the per subchannel power and the beamforming rank constraints. Two heuristic algorithms are designed. The proportional fairness hybrid beamforming algorithm provides the transmit precoder with a proportional fair spectral efficiency among users for the desired number of radio-frequency (RF) chains. Then, we transform the number of RF chains or rank constrained optimization problem into convex semidefinite programming (SDP) problem, which can be solved by standard techniques. Inspired by the formulated convex SDP problem, a low-complexity, two-step, PF-relaxed optimization algorithm has been provided for the formulated convex optimization problem. Simulation results show that the proposed suboptimal solution to the relaxed optimization problem is near-optimal for the signal-to-noise ratio SNR <= 10 dB and has a performance gap not greater than 2.33 b/s/Hz within the SNR range 0-25 dB. It also outperforms the maximum throughput and PF-based hybrid beamforming schemes for sum spectral efficiency, individual spectral efficiency, and fairness index
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