2,652 research outputs found

    A Non-Cooperative Game Theoretical Approach For Power Control In Virtual MIMO Wireless Sensor Network

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    Power management is one of the vital issue in wireless sensor networks, where the lifetime of the network relies on battery powered nodes. Transmitting at high power reduces the lifetime of both the nodes and the network. One efficient way of power management is to control the power at which the nodes transmit. In this paper, a virtual multiple input multiple output wireless sensor network (VMIMO-WSN)communication architecture is considered and the power control of sensor nodes based on the approach of game theory is formulated. The use of game theory has proliferated, with a broad range of applications in wireless sensor networking. Approaches from game theory can be used to optimize node level as well as network wide performance. The game here is categorized as an incomplete information game, in which the nodes do not have complete information about the strategies taken by other nodes. For virtual multiple input multiple output wireless sensor network architecture considered, the Nash equilibrium is used to decide the optimal power level at which a node needs to transmit, to maximize its utility. Outcome shows that the game theoretic approach considered for VMIMO-WSN architecture achieves the best utility, by consuming less power.Comment: 12 pages, 8 figure

    Maximum-Likelihood Sequence Detection of Multiple Antenna Systems over Dispersive Channels via Sphere Decoding

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    Multiple antenna systems are capable of providing high data rate transmissions over wireless channels. When the channels are dispersive, the signal at each receive antenna is a combination of both the current and past symbols sent from all transmit antennas corrupted by noise. The optimal receiver is a maximum-likelihood sequence detector and is often considered to be practically infeasible due to high computational complexity (exponential in number of antennas and channel memory). Therefore, in practice, one often settles for a less complex suboptimal receiver structure, typically with an equalizer meant to suppress both the intersymbol and interuser interference, followed by the decoder. We propose a sphere decoding for the sequence detection in multiple antenna communication systems over dispersive channels. The sphere decoding provides the maximum-likelihood estimate with computational complexity comparable to the standard space-time decision-feedback equalizing (DFE) algorithms. The performance and complexity of the sphere decoding are compared with the DFE algorithm by means of simulations

    Low-complexity iterative frequency domain decision feedback equalization

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    Single-carrier transmission with frequency domain equalization (SC-FDE) offers a viable design alternative to the classic orthogonal frequency division multiplexing technique. However, SC-FDE using a linear equalizer may suffer from serious performance deterioration for transmission over severely frequency-selective fading channels. An effective method of solving this problem is to introduce non-linear decision feedback equalization (DFE) to SC-FDE. In this contribution, a low complexity iterative decision feedback equalizer operating in the frequency domain of single-carrier systems is proposed. Based on the minimum mean square error criterion, a simplified parameter estimation method is introduced to calculate the coefficients of the feed-forward and feedback filters, which significantly reduces the implementation complexity of the equalizer. Simulation results show that the performance of the proposed simplified design is similar to the traditional iterative block DFE under various multipath fading channels but it imposes a much lower complexity than the latter
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