431 research outputs found

    Constrained power allocation schemes for coordinated base station transmission using block diagonalization

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    In this study, we propose several power allocation schemes in a coordinated base station downlink transmission with per antenna and per base station power constraints. Block Diagonalization is employed to remove interference among users. For each set of power constraints, two schemes based on the waterfilling distribution are proposed and compared to the optimal solution, which can only be obtained numerically by using convex optimization. We show that the proposed schemes achieve a performance, in terms of weighted sum rate, very close to the optimal, without the heavy computational complexity required by the latter. The sum rates are compared first in a simplified two-user two-cell case where we also compare our approach to the previous solutions available in the literature. Then, we examine the performance in a multi-cell scenario where we also evaluate the degradation of the performance caused by imperfect channel state informationThis study has been partly funded by projects TEC2008-06327-C03-02, CCG10-UC3M/TIC-4620, and CSD2008-00010.Publicad

    Achievable rate and fairness in coordinated base station transmission

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    This work focuses on the fairness in the distribution of the achievable rate per user in a cellular environment where clusters of base stations coordinate their transmissions in the downlink. Block Diagonalization is employed within the cluster to remove interference among users while the interference coming from other clusters remains. The probability distribution of the achievable rate per user shows a perfect match with a Gamma distribution so that a characterization in terms of mean and variance can provide a useful tool for the design of the clusters and the implementation of fairness strategies in a coordinated base station network with Block Diagonalization.This work is partly funded by the projects “GRE3N”: TEC2011-29006- C03-03, and “COMONSENS”: CSD2008-00010.Publicad

    Resource allocation for OFDMA systems with multi-cell joint transmission

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    This paper considers the downlink resource allocation of a coordinated multi-cell cluster in OFDMA systems with universal frequency reuse. Multi-cell joint transmission is considered via zero-forcing precoding. Furthermore, joint optimization of the user selection and power allocation across multiple subchannels and multiple cells is studied. The objective is to maximize the weighted sum rate under per-base-station power constraints. Based on general duality theory, two iterative resource allocation algorithms are proposed and compared with the optimal solution, which requires an exhaustive search of all possible combinations of users over all subchannels. Simulation results show that the two proposed algorithms achieve a performance very close to the optimal, with much lower computational complexity. In addition, we show that joint user set selection across multiple subchannels significantly improves the system performance in terms of the weighted sum rate

    Power allocation strategies for distributed precoded multicell based systems

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    Multicell cooperation is a promising solution for cellular wireless systems to mitigate intercell interference, improve system fairness, and increase capacity. In this article, we propose power allocation techniques for the downlink of distributed, precoded, multicell cellular-based systems. The precoder is designed in two phases: first the intercell interference is removed by applying a set of distributed precoding vectors; then the system is further optimized through power allocation. Three centralized power allocation algorithms with per-BS power constraint and diferente complexity trade-offs are proposed: one optimal in terms of minimization of the instantaneous average bit error rate (BER), and two suboptimal. In this latter approach, the powers are computed in two phases. First, the powers are derived under total power constraint (TPC) and two criterions are considered, namely, minimization of the instantaneous average BER and minimization of the sum of inverse of signal-to-noise ratio. Then, the final powers are computed to satisfy the individual per-BS power constraint. The performance of the proposed schemes is evaluated, considering typical pedestrian scenarios based on LTE specifications. The numerical results show that the proposed suboptimal schemes achieve a performance very close to the optimal but with lower computational complexity. Moreover, the performance of the proposed per-BS precoding schemes is close to the one obtained considering TPC over a supercell.Portuguese CADWIN - PTDC/ EEA TEL/099241/200

    Decomposition by Successive Convex Approximation: A Unifying Approach for Linear Transceiver Design in Heterogeneous Networks

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    We study the downlink linear precoder design problem in a multi-cell dense heterogeneous network (HetNet). The problem is formulated as a general sum-utility maximization (SUM) problem, which includes as special cases many practical precoder design problems such as multi-cell coordinated linear precoding, full and partial per-cell coordinated multi-point transmission, zero-forcing precoding and joint BS clustering and beamforming/precoding. The SUM problem is difficult due to its non-convexity and the tight coupling of the users' precoders. In this paper we propose a novel convex approximation technique to approximate the original problem by a series of convex subproblems, each of which decomposes across all the cells. The convexity of the subproblems allows for efficient computation, while their decomposability leads to distributed implementation. {Our approach hinges upon the identification of certain key convexity properties of the sum-utility objective, which allows us to transform the problem into a form that can be solved using a popular algorithmic framework called BSUM (Block Successive Upper-Bound Minimization).} Simulation experiments show that the proposed framework is effective for solving interference management problems in large HetNet.Comment: Accepted by IEEE Transactions on Wireless Communicatio

    Mean Achievable Rates in Clustered Coordinated Base Station Transmission with Block Diagonalization

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    We focus on the mean achievable rate per user of the coordinated base station downlink transmission in a clustered cellular environment, with transmit power constraints at the base stations. Block Diagonalization is employed within the cluster to remove interference among users while the interference from other clusters remains. The average achievable rate per user is evaluated considering the effects of the propagation channel and the interference and a theoretical framework is presented to provide its analytical expression, validated by simulation results with different power allocation schemes. As an application, the number of cells of the cluster that maximizes the mean achievable rate per user is investigated. It can be seen that in most of the cases a reduced cluster size, close to seven cells, guarantees a rate very close to the maximum achievableThis work is partly funded by projects "GRE3N": TEC2011-29006-C03-03 and "COMONSENS": CSD2008-00010En-prens

    Improved Linear Precoding over Block Diagonalization in Multi-cell Cooperative Networks

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    In downlink multiuser multiple-input multiple-output (MIMO) systems, block diagonalization (BD) is a practical linear precoding scheme which achieves the same degrees of freedom (DoF) as the optimal linear/nonlinear precoding schemes. However, its sum-rate performance is rather poor in the practical SNR regime due to the transmit power boost problem. In this paper, we propose an improved linear precoding scheme over BD with a so-called "effective-SNR-enhancement" technique. The transmit covariance matrices are obtained by firstly solving a power minimization problem subject to the minimum rate constraint achieved by BD, and then properly scaling the solution to satisfy the power constraints. It is proved that such approach equivalently enhances the system SNR, and hence compensates the transmit power boost problem associated with BD. The power minimization problem is in general non-convex. We therefore propose an efficient algorithm that solves the problem heuristically. Simulation results show significant sum rate gains over the optimal BD and the existing minimum mean square error (MMSE) based precoding schemes.Comment: 21 pages, 4 figure
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