47,994 research outputs found
An efficient power control game model for wireless sensor networks
Efficient energy usage is a major design challenge in wireless sensor networks. In this paper, an efficient power control scheme that mitigates interference and reduces the energy usage of the sensor nodes in a wireless sensor network is presented using the game theory. A non-cooperative game was formulated among the sensor nodes in the modeled network by setting a transmission power limit at the receiving nodes which ensured that the transmitting nodes transmits at the optimal power level. The utility of the sensor nodes and the interference proportion within the network was evaluated at the optimal and discrete transmit powers. The Nash equilibrium of the proposed game was studied and it corresponds to a stability point where the network performance was optimized. Simulation results showed that the proposed scheme is effective for optimization of network resource utilization, reduction in the energy consumption of the nodes, increasing the transmission sum rate, reduction of interference within the network, and improving the network capacity. Keywords: Power control, Wireless sensor network, Non-cooperative game, Interference, Energ
Stable Wireless Network Control Under Service Constraints
We consider the design of wireless queueing network control policies with
particular focus on combining stability with additional application-dependent
requirements. Thereby, we consequently pursue a cost function based approach
that provides the flexibility to incorporate constraints and requirements of
particular services or applications. As typical examples of such requirements,
we consider the reduction of buffer underflows in case of streaming traffic,
and energy efficiency in networks of battery powered nodes. Compared to the
classical throughput optimal control problem, such requirements significantly
complicate the control problem. We provide easily verifyable theoretical
conditions for stability, and, additionally, compare various candidate cost
functions applied to wireless networks with streaming media traffic. Moreover,
we demonstrate how the framework can be applied to the problem of energy
efficient routing, and we demonstrate the aplication of our framework in
cross-layer control problems for wireless multihop networks, using an advanced
power control scheme for interference mitigation, based on successive convex
approximation. In all scenarios, the performance of our control framework is
evaluated using extensive numerical simulations.Comment: Accepted for publication in IEEE Transactions on Control of Network
Systems. arXiv admin note: text overlap with arXiv:1208.297
Wireless Information Transfer with Opportunistic Energy Harvesting
Energy harvesting is a promising solution to prolong the operation of
energy-constrained wireless networks. In particular, scavenging energy from
ambient radio signals, namely wireless energy harvesting (WEH), has recently
drawn significant attention. In this paper, we consider a point-to-point
wireless link over the narrowband flat-fading channel subject to time-varying
co-channel interference. It is assumed that the receiver has no fixed power
supplies and thus needs to replenish energy opportunistically via WEH from the
unintended interference and/or the intended signal sent by the transmitter. We
further assume a single-antenna receiver that can only decode information or
harvest energy at any time due to the practical circuit limitation. Therefore,
it is important to investigate when the receiver should switch between the two
modes of information decoding (ID) and energy harvesting (EH), based on the
instantaneous channel and interference condition. In this paper, we derive the
optimal mode switching rule at the receiver to achieve various trade-offs
between wireless information transfer and energy harvesting. Specifically, we
determine the minimum transmission outage probability for delay-limited
information transfer and the maximum ergodic capacity for no-delay-limited
information transfer versus the maximum average energy harvested at the
receiver, which are characterized by the boundary of so-called "outage-energy"
region and "rate-energy" region, respectively. Moreover, for the case when the
channel state information (CSI) is known at the transmitter, we investigate the
joint optimization of transmit power control, information and energy transfer
scheduling, and the receiver's mode switching. Our results provide useful
guidelines for the efficient design of emerging wireless communication systems
powered by opportunistic WEH.Comment: to appear in IEEE Transactions on Wireless Communicatio
Introducing Hierarchy in Energy Games
In this work we introduce hierarchy in wireless networks that can be modeled
by a decentralized multiple access channel and for which energy-efficiency is
the main performance index. In these networks users are free to choose their
power control strategy to selfishly maximize their energy-efficiency.
Specifically, we introduce hierarchy in two different ways: 1. Assuming
single-user decoding at the receiver, we investigate a Stackelberg formulation
of the game where one user is the leader whereas the other users are assumed to
be able to react to the leader's decisions; 2. Assuming neither leader nor
followers among the users, we introduce hierarchy by assuming successive
interference cancellation at the receiver. It is shown that introducing a
certain degree of hierarchy in non-cooperative power control games not only
improves the individual energy efficiency of all the users but can also be a
way of insuring the existence of a non-saturated equilibrium and reaching a
desired trade-off between the global network performance at the equilibrium and
the requested amount of signaling. In this respect, the way of measuring the
global performance of an energy-efficient network is shown to be a critical
issue.Comment: Accepted for publication in IEEE Trans. on Wireless Communication
IACR: an interference-aware channel reservation for wireless sensor networks
In battery-based wireless sensor networks, energy-efficient operation is one of the most important factors. Especially, in order to improve energy efficiency in wireless sensor networks, various studies on low power operation have been actively conducted in the MAC layer. In recent years, mutual interference among various radio technologies using the same radio frequency band has become a serious problem. Wi-Fi, ZigBee, and Bluetooth use the same frequency band of 2.4GHz at the same time, which causes various signal interference problems. In this paper, we propose a novel channel reservation scheme, called IACR, to improve the energy efficiency of wireless sensor networks in an environment where interference occurs between various wireless technologies. The proposed scheme inserts a PN code into a long preamble for exchanging transmission status information between a transmitting node and a receiving node, thereby improving the transmission success probability while receiving less influence on transmission of other radio technologies. We performed an event-driven simulation and an experiment to measure the signal detection rate. As a result, it can be seen that the proposed technique reduces the packet drop rate by 15% and increases the discoverable distance of the control packet for channel reservation
Dynamic and Channel Adaptive Error Control Scheme in Wireless Sensor Networks
The application of wireless technology is increasingly influencing the deployment of sensor networks at low cost and maintainance in all walks of life. Poor channel conditions, severe power constraints, fading, interference and the low power communication requirements magnify the need for energy efficient and preferably cross layer error control schemes in Wireless Sensor Networks (WSNs). The main goal of error control mechanisms in WSNs is to reduce the energy expenditure while taking care of reliable and fast delivery of the sensed data. In this paper, we propose a FFFD;Dynamic and Channel Adaptive Error Control Scheme in Wireless Sensor NetworksFFFD; (DCAECS) that estimates the channel errors and controls errors dynamically based on channel characteristics and noise power observed at the receiver. This motivates the error control strategy to vary as the channel conditions change in terms of noise level. In this paper, we have come up with the models for both the error and channel estimation. Analysis and simulation results for various message sizes and error conditions show that there is an improvement in terms of throughput, BER and the probability of retransmission as compared to FFFD;ARQ Scheme With Adaptive Error ControlFFFD; (ASAEC)
Efficient radio resource management for future generation heterogeneous wireless networks
The heterogeneous deployment of small cells (e.g., femtocells) in the coverage area of the traditional macrocells is a cost-efficient solution to provide network capacity, indoor coverage and green communications towards sustainable environments in the future fifth generation (5G) wireless networks. However, the unplanned and ultra-dense deployment of femtocells with their uncoordinated operations will result in technical challenges such as severe interference, a significant increase in total energy consumption, unfairness in radio resource sharing and inadequate quality of service provisioning. Therefore, there is a need to develop efficient radio resource management algorithms that will address the above-mentioned technical challenges. The aim of this thesis is to develop and evaluate new efficient radio resource management algorithms that will be implemented in cognitive radio enabled femtocells to guarantee the economical sustainability of broadband wireless communications and users' quality of service in terms of throughput and fairness. Cognitive Radio (CR) technology with the Dynamic Spectrum Access (DSA) and stochastic process are the key technologies utilized in this research to increase the spectrum efficiency and energy efficiency at limited interference. This thesis essentially investigates three research issues relating to the efficient radio resource management: Firstly, a self-organizing radio resource management algorithm for radio resource allocation and interference management is proposed. The algorithm considers the effect of imperfect spectrum sensing in detecting the available transmission opportunities to maximize the throughput of femtocell users while keeping interference below pre-determined thresholds and ensuring fairness in radio resource sharing among users. Secondly, the effect of maximizing the energy efficiency and the spectrum efficiency individually on radio resource management is investigated. Then, an energy-efficient radio resource management algorithm and a spectrum-efficient radio resource management algorithm are proposed for green communication, to improve the probabilities of spectrum access and further increase the network capacity for sustainable environments. Also, a joint maximization of the energy efficiency and spectrum efficiency of the overall networks is considered since joint optimization of energy efficiency and spectrum efficiency is one of the goals of 5G wireless networks. Unfortunately, maximizing the energy efficiency results in low performance of the spectrum efficiency and vice versa. Therefore, there is an investigation on how to balance the trade-off that arises when maximizing both the energy efficiency and the spectrum efficiency simultaneously. Hence, a joint energy efficiency and spectrum efficiency trade-off algorithm is proposed for radio resource allocation in ultra-dense heterogeneous networks based on orthogonal frequency division multiple access. Lastly, a joint radio resource allocation with adaptive modulation and coding scheme is proposed to minimize the total transmit power across femtocells by considering the location and the service requirements of each user in the network. The performance of the proposed algorithms is evaluated by simulation and numerical analysis to demonstrate the impact of ultra-dense deployment of femtocells on the macrocell networks. The results show that the proposed algorithms offer improved performance in terms of throughput, fairness, power control, spectrum efficiency and energy efficiency. Also, the proposed algorithms display excellent performance in dynamic wireless environments
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