1,011 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
Review on Radio Resource Allocation Optimization in LTE/LTE-Advanced using Game Theory
Recently, there has been a growing trend toward ap-plying game theory (GT) to various engineering fields in order to solve optimization problems with different competing entities/con-tributors/players. Researches in the fourth generation (4G) wireless network field also exploited this advanced theory to overcome long term evolution (LTE) challenges such as resource allocation, which is one of the most important research topics. In fact, an efficient de-sign of resource allocation schemes is the key to higher performance. However, the standard does not specify the optimization approach to execute the radio resource management and therefore it was left open for studies. This paper presents a survey of the existing game theory based solution for 4G-LTE radio resource allocation problem and its optimization
Multicast Scheduling and Resource Allocation Algorithms for OFDMA-Based Systems: A Survey
Multicasting is emerging as an enabling technology
for multimedia transmissions over wireless networks to support several groups of users with flexible quality of service (QoS)requirements. Although multicast has huge potential to push the limits of next generation communication systems; it is however one of the most challenging issues currently being addressed. In this survey, we explain multicast group formation and various
forms of group rate determination approaches. We also provide a systematic review of recent channel-aware multicast scheduling and resource allocation (MSRA) techniques proposed for downlink multicast services in OFDMA based systems. We study these enabling algorithms, evaluate their core characteristics, limitations and classify them using multidimensional matrix. We cohesively review the algorithms in terms of their throughput maximization, fairness considerations, performance complexities,
multi-antenna support, optimality and simplifying assumptions. We discuss existing standards employing multicasting and further highlight some potential research opportunities in multicast systems
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Cross-layer design for OFDMA wireless networks with finite queue length based on game theory
This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University London.In next generation wireless networks such as 4G- LTE and WiMax, the demand for high data rates, the scarcity of wireless resources and the time varying channel conditions has led to the adoption of more sophisticated and robust techniques in PHY such as orthogonal frequency division multiplexing (OFDM) and the corresponding access technique known as orthogonal frequency division multiplexing access (OFDMA). Cross-layer schedulers have been developed in order to describe the procedure of resource allocation in OFDMA wireless networks. The resource allocation in OFDMA wireless networks has received great attention in research, by proposing many different ways for frequency diversity exploitation and system’s optimization. Many cross-layer proposals for dynamic resource allocation have been investigated in literature approaching the optimization problem from different viewpoints i.e. maximizing total data rate, minimizing total transmit power, satisfying minimum users’ requirements or providing fairness amongst users. The design of a cross-layer scheduler for OFDMA wireless networks is the topic of this research. The scheduler utilizes game theory in order to make decisions for subcarrier and power allocation to the users with the main concern being to maintain fairness as well as to maximize overall system’s performance. A very well known theorem in cooperative game theory, the Nash Bargaining Solution (NBS), is employed and solved in a close form way, resulting in a Pareto optimal solution. Two different cases are proposed. The first one is the symmetric NBS (S-NBS) where all users have the same weight and therefore all users have the same opportunity for resources and the second one, is the asymmetric NBS (A-NBS), where users have different weights, hence different priorities where the scheduler favours users with higher priorities at expense of lower priority users. As MAC layer is vital for cross-layer, the scheduler is combined with a queuing model based on Markov chain in order to describe more realistically the incoming procedure from the higher layers
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