Power allocation for statistical qo s provisioning in opportunistic multi relay df cognitive networks

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POWER ALLOCATION FOR STATISTICAL QOS PROVISIONING IN
OPPORTUNISTIC MULTI-RELAY DF COGNITIVE NETWORKS
ABSTRACT:
We propose a power allocation scheme for statistical quality-of-service (QoS) provisioning in
multi-relay decode-and-forward (DF) cognitive networks (CN). By considering the direct link
between the source and destination, the CN first chooses the transmission mode (direct
transmission or relay transmission) based on the channel state information. Then, according to
the determined transmission mode, efficient power allocation will be performed under the given
QoS requirement, the average transmit and interference power constraints as well as the peak
interference constraint.
Our proposed power allocation scheme indicates that, in order to achieve the maximum
throughput, at most two relays can be involved for the transmission. Simulation results show that
our proposed scheme outperforms the max-min criterion and equal power allocation policy.
ECWAY TECHNOLOGIES
IEEE PROJECTS & SOFTWARE DEVELOPMENTS
OUR OFFICES @ CHENNAI / TRICHY / KARUR / ERODE / MADURAI / SALEM / COIMBATORE
CELL: +91 98949 17187, +91 875487 2111 / 3111 / 4111 / 5111 / 6111
VISIT: www.ecwayprojects.com MAIL TO: ecwaytechnologies@gmail.com

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In an era where communication has a most important role in modern societies, designing efficient algorithms for data transmission is of the outmost importance. TDMA is a technology used in many communication systems such as satellite, cell phone as well as other wireless or mobile networks. Most 2G cellular systems as well as some 3G are TDMA based. In order to transmit data in such systems we need to cluster them in packages. To achieve a faster transmission we are allowed to preempt the transmission of any packet in order to resume at a later time. Preemption can be used to reduce idleness of some stations. Such preemptions though come with a reconfiguration cost in order to setup for the next transmission. In this paper we propose two algorithms which yield improved transmission scheduling. These two algorithms we call MGA and IMGA (Improved MGA). We have proven an approximation ratio for MGA and ran experiments to establish that it works even better in practice. In order to conclude that MGA will be a very helpful tool in constructing an improved schedule for packet routing using preemtion with a setup cost, we compare its results to two other efficient algorithms designed by researchers in the past: A-PBS(d+1) and GWA. To establish the efficiency of IMGA we ran experiments in comparison to MGA as well as APBS(d+1) and GWA. IMGA has proven to produce the most efficient schedule on all counts.

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Power allocation for statistical qo s provisioning in opportunistic multi relay df cognitive networks

1. POWER ALLOCATION FOR STATISTICAL QOS PROVISIONING IN OPPORTUNISTIC MULTI-RELAY DF COGNITIVE NETWORKS ABSTRACT: We propose a power allocation scheme for statistical quality-of-service (QoS) provisioning in multi-relay decode-and-forward (DF) cognitive networks (CN). By considering the direct link between the source and destination, the CN first chooses the transmission mode (direct transmission or relay transmission) based on the channel state information. Then, according to the determined transmission mode, efficient power allocation will be performed under the given QoS requirement, the average transmit and interference power constraints as well as the peak interference constraint. Our proposed power allocation scheme indicates that, in order to achieve the maximum throughput, at most two relays can be involved for the transmission. Simulation results show that our proposed scheme outperforms the max-min criterion and equal power allocation policy. ECWAY TECHNOLOGIES IEEE PROJECTS & SOFTWARE DEVELOPMENTS OUR OFFICES @ CHENNAI / TRICHY / KARUR / ERODE / MADURAI / SALEM / COIMBATORE CELL: +91 98949 17187, +91 875487 2111 / 3111 / 4111 / 5111 / 6111 VISIT: www.ecwayprojects.com MAIL TO: ecwaytechnologies@gmail.com

Power allocation for statistical qo s provisioning in opportunistic multi relay df cognitive networks

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