1,518 research outputs found
Relay selection for multiple access relay channel with decode-forward and analog network coding
This paper presents a relay selection for decode-and-forward based on network
coding (DF-NC) and analog-NC protocols in general scheme of cellular network
system. In the propose scheme the two source node simultaneously transmit their
own information to all the relays as well as the destination node, and then, a
single relay i.e. best with a minimum symbol error rate (SER) will be selected
to forward the new version of the received signal. Simulation results show
that, the DF-NC scheme with considerable performance has exactness over
analog-NC scheme. To improve the system performance, optimal power allocation
between the two sources and the best relay is determined based on the
asymptotic SER. By increasing the number of relays node, the optimum power
allocation achieve better performance than asymptotic SER.Comment: 11 pages, 5 figures; International Journal of Distributed and
Parallel Systems (IJDPS) Vol.3, No.2, March 201
Decentralized Dynamic Hop Selection and Power Control in Cognitive Multi-hop Relay Systems
In this paper, we consider a cognitive multi-hop relay secondary user (SU)
system sharing the spectrum with some primary users (PU). The transmit power as
well as the hop selection of the cognitive relays can be dynamically adapted
according to the local (and causal) knowledge of the instantaneous channel
state information (CSI) in the multi-hop SU system. We shall determine a low
complexity, decentralized algorithm to maximize the average end-to-end
throughput of the SU system with dynamic spatial reuse. The problem is
challenging due to the decentralized requirement as well as the causality
constraint on the knowledge of CSI. Furthermore, the problem belongs to the
class of stochastic Network Utility Maximization (NUM) problems which is quite
challenging. We exploit the time-scale difference between the PU activity and
the CSI fluctuations and decompose the problem into a master problem and
subproblems. We derive an asymptotically optimal low complexity solution using
divide-and-conquer and illustrate that significant performance gain can be
obtained through dynamic hop selection and power control. The worst case
complexity and memory requirement of the proposed algorithm is O(M^2) and
O(M^3) respectively, where is the number of SUs
Energy-Efficient Power Control for Multiple-Relay Cooperative Networks Using Q-Learning
In this paper, we investigate the power control problem in a cooperative network with multiple wireless transmitters, multiple amplify-and-forward relays, and one destination. The relay communication can be either full duplex or half-duplex, and all source nodes interfere with each other at every intermediate relay node, and all active nodes (transmitters and relay nodes) interfere with each other at the base station. A game-theory-based power control algorithm is devised to allocate the powers among all active nodes. The source nodes aim at maximizing their energy efficiency (in bits per Joule per Hertz), whereas the relays aim at maximizing the network sum rate. We show that the proposed game admits multiple pure/mixed-strategy Nash equilibrium points. A Q-learning-based algorithm is then formulated to let the active players converge to the best Nash equilibrium point that combines good performance in terms of both energy efficiency and overall data rate. Numerical results show that the full-duplex scheme outperforms half-duplex configuration, Nash bargaining solution, the max-min fairness, and the max-rate optimization schemes in terms of energy efficiency, and outperforms the half-duplex mode, Nash bargaining system, and the max-min fairness scheme in terms of network sum rate
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