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1. Power Allocation for Statistical QoS Provisioning in
Opportunistic Multi-Relay DF Cognitive Networks
Abstract
In this letter, 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.
Existing system
The deterministic delay QoS guarantee is usually unrealistic for practical wireless networks. Consequently, the
statistical version should be employed for the CN’s delay QoS provisioning. Furthermore, resource allocation
and relay communications have been regarded as two powerful approaches to improve the CN’s performance.
However, most researches on resource allocation for cognitive relay networks are mainly towards maximizing
the Shannon capacity without guaranteeing the delay-QoS requirements. Therefore, there is an urgent need to
develop the effiresource allocation scheme for cognitive relay networks with statistically guaranteed delay QoS.
In this letter, we propose a statistical QoS driven power allocation scheme for multi-relay decode-and-forward
(DF) CN. The CN can dynamically choose the transmission mode (direct transmission or relay transmission),
perform the relay selection, and allocate the upper-bounded transmit power across the source and selected relays
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2. based on the channel state information. Our proposed power allocation scheme not only satisfies the given QoS
requirement, but also meets a series of imposed transmit and interference power constraints. Moreover, we find
that, in order to maximize the CN’s throughput, at most two relays can be involved for the transmission.
Disadvantages
The message to SD. The PS transmits with constant power. The SS and SRs adjust their transmit power
based on the NGV and the statistical QoS requirement.
Because effective capacity can be regarded as the maximum available throughput of the wireless
network under the givenQoS requirement.
Proposed System
The 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. Our proposed power allocation scheme not only satisfies the
given QoS requirement, but also meets a series of imposed transmit and interference power constraints.
Moreover, we find that, in order to maximize the CN’s throughput, at most two relays can be involved for the
transmission. In this section, we evaluate our proposed power allocation scheme through simulations. In our
simulations, we set the frame duration , the bandwidth , the Nakagami parameter , the constant transmit power
of the PN , the maximum average transmit power the maximum average interference power and the maximum
peak interference power.
Advantages
The normalized effective capacities of the CN under three different power allocation schemes, which are
our proposed power allocation scheme, max-min criterion, and equal power allocation policy,
respectively.
That our proposed power allocation scheme outperforms the max-min criterion and equal power
allocation policy for various QoS exponents.
The max-min criterion and equal power allocation policy and thus can achieve better effective capacity.

3. Module Description
Cognitive network
To meet not only the transmit power constraint, but also the predefined interference power requirement
imposed by the primary network, the delay Quality-of-Service.
Qos Driven Power Allocation
To develop an efficient power allocation scheme to maximize the available throughput of the multi-relay DF
CN under the given statistical QoS requirement. The statistical QoS provisioning is described by the delay-
bound violation probability/
Effective capacity
The delay and predefined delay bound, respectively, and is the maximum violation probability. Effective
bandwidth and effective capacity are powerful approaches to calculate the delay-bound violation probability.
Consider a stable dynamic discrete-time queuing system with arrival rate and service rate.
Relay Transmission
That belongs to should participate the transmission. Consequently, we first find the optimal power allocation
scheme for any given relay set. Then, we determine the optimal relay set . For any given relay set, the service
rate is determined.
Equal power allocation
The equal power allocation policy for various QoS exponents. The presents the utilized average transmit power
of the CN and the average interference power perceived by the PN under the three power allocation schemes.
We can observe from that the average interference power under the three schemes all meet the maximum
average interference power. However, our proposed power allocation scheme can more sufficiently utilize the
upper-bounded power resource than the max-min criterion and equal power allocation policy and thus can
achieve better effective capacity.
CONCLUSIONS
We proposed an efficient power allocation scheme for statistical QoS provisioning in multi-relay
decode-and-forward cognitive networks subject to the average transmit and interference power constraints as
well as the peak interference constraint. Simulation results show that our proposed power allocation scheme
outperforms themax-min criterion and equal power allocation policy.

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