924 resultados para Cooperative MIMO


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It is well known that multiple-input multiple-output (MIMO) techniques can bring numerous benefits, such as higher spectral efficiency, to point-to-point wireless links. More recently, there has been interest in extending MIMO concepts tomultiuser wireless systems. Our focus in this paper is on network MIMO, a family of techniques whereby each end user in a wireless access network is served through several access points within its range of influence. By tightly coordinating the transmission and reception of signals at multiple access points, network MIMO can transcend the limits on spectral efficiency imposed by cochannel interference. Taking prior information-theoretic analyses of networkMIMO to the next level, we quantify the spectral efficiency gains obtainable under realistic propagation and operational conditions in a typical indoor deployment. Our study relies on detailed simulations and, for specificity, is conducted largely within the physical-layer framework of the IEEE 802.16e Mobile WiMAX system. Furthermore,to facilitate the coordination between access points, we assume that a high-capacity local area network, such as Gigabit Ethernet,connects all the access points. Our results confirm that network MIMO stands to provide a multiple-fold increase in spectralefficiency under these conditions.

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Wireless “MIMO” systems, employing multiple transmit and receive antennas, promise a significant increase of channel capacity, while orthogonal frequency-division multiplexing (OFDM) is attracting a good deal of attention due to its robustness to multipath fading. Thus, the combination of both techniques is an attractive proposition for radio transmission. The goal of this paper is the description and analysis of a new and novel pilot-aided estimator of multipath block-fading channels. Typical models leading to estimation algorithms assume the number of multipath components and delays to be constant (and often known), while their amplitudes are allowed to vary with time. Our estimator is focused instead on the more realistic assumption that the number of channel taps is also unknown and varies with time following a known probabilistic model. The estimation problem arising from these assumptions is solved using Random-Set Theory (RST), whereby one regards the multipath-channel response as a single set-valued random entity.Within this framework, Bayesian recursive equations determine the evolution with time of the channel estimator. Due to the lack of a closed form for the solution of Bayesian equations, a (Rao–Blackwellized) particle filter (RBPF) implementation ofthe channel estimator is advocated. Since the resulting estimator exhibits a complexity which grows exponentially with the number of multipath components, a simplified version is also introduced. Simulation results describing the performance of our channel estimator demonstrate its effectiveness.

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In a MIMO layered architecture, several codewordsare transmitted from a multiplicity of antennas. Although thespectral efficiency is maximized if the rates of these codewordsare separately controlled, the feedback rate within the linkadaptation loop is reduced if they are constrained to be identical.This poses a direct tradeoff between performance andfeedback overhead. This paper provides analytical expressionsthat quantify the difference in spectral efficiency between bothapproaches for arbitrary numbers of antennas. Specifically, thecharacterization takes place in the realm of the low- and highpowerregimes via expansions that are shown to have a widerange of validity.In addition, the possibility of adjusting the transmit powerof each codeword individually is considered as an alternative tothe separate control of their rates. Power allocation, however,turns out to be inferior to rate control within the context of thisproblem.

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In this paper, we introduce a pilot-aided multipath channel estimator for Multiple-Input Multiple-Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) systems. Typical estimation algorithms assume the number of multipath components and delays to be known and constant, while theiramplitudes may vary in time. In this work, we focus on the more realistic assumption that also the number of channel taps is unknown and time-varying. The estimation problem arising from this assumption is solved using Random Set Theory (RST), which is a probability theory of finite sets. Due to the lack of a closed form of the optimal filter, a Rao-Blackwellized Particle Filter (RBPF) implementation of the channel estimator is derived. Simulation results demonstrate the estimator effectiveness.

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For single-user MIMO communication with uncoded and coded QAM signals, we propose bit and power loading schemes that rely only on channel distribution information at the transmitter. To that end, we develop the relationship between the average bit error probability at the output of a ZF linear receiver and the bit rates and powers allocated at the transmitter. This relationship, and the fact that a ZF receiver decouples the MIMO parallel channels, allow leveraging bit loading algorithms already existing in the literature. We solve dual bit rate maximization and power minimization problems and present performance resultsthat illustrate the gains of the proposed scheme with respect toa non-optimized transmission.

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A contemporary perspective on the tradeoff between transmit antenna diversity and spatial multi-plexing is provided. It is argued that, in the context of modern cellular systems and for the operating points of interest, transmission techniques that utilize all available spatial degrees of freedom for multiplexingoutperform techniques that explicitly sacrifice spatialmultiplexing for diversity. Reaching this conclusion, however, requires that the channel and some key system features be adequately modeled; failure to do so may bring about starkly different conclusions. As a specific example, this contrast is illustrated using the 3GPP Long-Term Evolution system design.

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A systolic array to implement lattice-reduction-aided lineardetection is proposed for a MIMO receiver. The lattice reductionalgorithm and the ensuing linear detections are operated in the same array, which can be hardware-efficient. All-swap lattice reduction algorithm (ASLR) is considered for the systolic design.ASLR is a variant of the LLL algorithm, which processes all lattice basis vectors within one iteration. Lattice-reduction-aided linear detection based on ASLR and LLL algorithms have very similarbit-error-rate performance, while ASLR is more time efficient inthe systolic array, especially for systems with a large number ofantennas.

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Explaining the evolution of sociality is challenging because social individuals face disadvantages that must be balanced by intrinsic benefits of living in a group. One potential route towards the evolution of sociality may emerge from the avoidance of dispersal, which can be risky in some environments. Although early studies found that local competition may cancel the benefits of cooperation in viscous populations, subsequent studies have identified conditions, such as the presence of kin recognition or specific demographic conditions, under which altruism will still spread. Most of these studies assume that the costs of cooperating outweigh the direct benefits (strong altruism). In nature, however, many organisms gain synergistic benefits from group living, which may counterbalance even costly altruistic behaviours. Here, we use an individual based model to investigate how dispersal and social behaviour co-evolve when social behaviours result in synergistic benefits that counterbalance the relative cost of altruism to a greater extent than assumed in previous models. When the cost of cooperation is high, selection for sociality responds strongly to the cost of dispersal. In particular, cooperation can begin to spread in a population when higher cooperation levels become correlated with lower dispersal tendencies within individuals. In contrast, less costly social behaviours are less sensitive to the cost of dispersal. In line with previous studies, we find that mechanisms of global population control also affect this relationship: when whole patches (groups) go extinct each generation, selection favours a relatively high dispersal propensity, and social behaviours evolve only when they are not very costly. If random individuals within groups experience mortality each generation to maintain a global carrying capacity, on the other hand, social behaviours spread and dispersal is reduced, even when the latter is not costly.

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In this paper we view bargaining and cooperation as an interaction superimposed on a strategic form game. A multistage bargaining procedure for N players, the proposer commitment procedure, is presented. It is inspired by Nash s two-player variable-threat model; a key feature is the commitment to threats. We establish links to classical cooperative game theory solutions, such as the Shapley value in the transferable utility case. However, we show that even in standard pure exchange economies the traditional coalitional function may not be adequate when utilities are not transferable.

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Water fact sheet for Iowa Department of Natural Resources and the Geological Bureau.

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Water fact sheet for Iowa Department of Natural Resources and the Geological Bureau.

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Water fact sheet for Iowa Department of Natural Resources and the Geological Bureau.

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Water fact sheet for Iowa Department of Natural Resources and the Geological Bureau.

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Water fact sheet for Iowa Department of Natural Resources and the Geological Bureau.