2,063 research outputs found
Enhancing Physical Layer Security in AF Relay Assisted Multi-Carrier Wireless Transmission
In this paper, we study the physical layer security (PLS) problem in the dual
hop orthogonal frequency division multiplexing (OFDM) based wireless
communication system. First, we consider a single user single relay system and
study a joint power optimization problem at the source and relay subject to
individual power constraint at the two nodes. The aim is to maximize the end to
end secrecy rate with optimal power allocation over different sub-carriers.
Later, we consider a more general multi-user multi-relay scenario. Under high
SNR approximation for end to end secrecy rate, an optimization problem is
formulated to jointly optimize power allocation at the BS, the relay selection,
sub-carrier assignment to users and the power loading at each of the relaying
node. The target is to maximize the overall security of the system subject to
independent power budget limits at each transmitting node and the OFDMA based
exclusive sub-carrier allocation constraints. A joint optimization solution is
obtained through duality theory. Dual decomposition allows to exploit convex
optimization techniques to find the power loading at the source and relay
nodes. Further, an optimization for power loading at relaying nodes along with
relay selection and sub carrier assignment for the fixed power allocation at
the BS is also studied. Lastly, a sub-optimal scheme that explores joint power
allocation at all transmitting nodes for the fixed subcarrier allocation and
relay assignment is investigated. Finally, simulation results are presented to
validate the performance of the proposed schemes.Comment: 10 pages, 7 figures, accepted in Transactions on Emerging
Telecommunications Technologies (ETT), formerly known as European
Transactions on Telecommunications (ETT
Energy-efficiency for MISO-OFDMA based user-relay assisted cellular networks
The concept of improving energy-efficiency (EE) without sacrificing the service quality has become important nowadays. The combination of orthogonal frequency-division multiple-access (OFDMA) multi-antenna transmission technology and relaying is one of the key technologies to deliver the promise of reliable and high-data-rate coverage in the most cost-effective manner. In this paper, EE is studied for the downlink multiple-input single-output (MISO)-OFDMA based user-relay assisted cellular networks. EE maximization is formulated for decode and forward (DF) relaying scheme with the consideration of both transmit and circuit power consumption as well as the data rate requirements for the mobile users. The quality of-service (QoS)-constrained EE maximization, which is defined for multi-carrier, multi-user, multi-relay and multi-antenna networks, is a non-convex and combinatorial problem so it is hard to tackle. To solve this difficult problem, a radio resource management (RRM) algorithm that solves the subcarrier allocation, mode selection and power allocation separately is proposed. The efficiency of the proposed algorithm is demonstrated by numerical results for different system parameter
Optimal Distributed Resource Allocation for Decode-and-Forward Relay Networks
This paper presents a distributed resource allocation algorithm to jointly
optimize the power allocation, channel allocation and relay selection for
decode-and-forward (DF) relay networks with a large number of sources, relays,
and destinations. The well-known dual decomposition technique cannot directly
be applied to resolve this problem, because the achievable data rate of DF
relaying is not strictly concave, and thus the local resource allocation
subproblem may have non-unique solutions. We resolve this non-strict concavity
problem by using the idea of the proximal point method, which adds quadratic
terms to make the objective function strictly concave. However, the proximal
solution adds an extra layer of iterations over typical duality based
approaches, which can significantly slow down the speed of convergence. To
address this key weakness, we devise a fast algorithm without the need for this
additional layer of iterations, which converges to the optimal solution. Our
algorithm only needs local information exchange, and can easily adapt to
variations of network size and topology. We prove that our distributed resource
allocation algorithm converges to the optimal solution. A channel resource
adjustment method is further developed to provide more channel resources to the
bottleneck links and realize traffic load balance. Numerical results are
provided to illustrate the benefits of our algorithm
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