1,478 research outputs found

    AirSync: Enabling Distributed Multiuser MIMO with Full Spatial Multiplexing

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    The enormous success of advanced wireless devices is pushing the demand for higher wireless data rates. Denser spectrum reuse through the deployment of more access points per square mile has the potential to successfully meet the increasing demand for more bandwidth. In theory, the best approach to density increase is via distributed multiuser MIMO, where several access points are connected to a central server and operate as a large distributed multi-antenna access point, ensuring that all transmitted signal power serves the purpose of data transmission, rather than creating "interference." In practice, while enterprise networks offer a natural setup in which distributed MIMO might be possible, there are serious implementation difficulties, the primary one being the need to eliminate phase and timing offsets between the jointly coordinated access points. In this paper we propose AirSync, a novel scheme which provides not only time but also phase synchronization, thus enabling distributed MIMO with full spatial multiplexing gains. AirSync locks the phase of all access points using a common reference broadcasted over the air in conjunction with a Kalman filter which closely tracks the phase drift. We have implemented AirSync as a digital circuit in the FPGA of the WARP radio platform. Our experimental testbed, comprised of two access points and two clients, shows that AirSync is able to achieve phase synchronization within a few degrees, and allows the system to nearly achieve the theoretical optimal multiplexing gain. We also discuss MAC and higher layer aspects of a practical deployment. To the best of our knowledge, AirSync offers the first ever realization of the full multiuser MIMO gain, namely the ability to increase the number of wireless clients linearly with the number of jointly coordinated access points, without reducing the per client rate.Comment: Submitted to Transactions on Networkin

    Exploiting Interference Alignment in Multi-Cell Cooperative OFDMA Resource Allocation

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    This paper studies interference alignment (IA) based multi-cell cooperative resource allocation for the downlink OFDMA with universal frequency reuse. Unlike the traditional scheme that treats subcarriers as separate dimensions for resource allocation, the IA technique is utilized to enable frequency-domain precoding over parallel subcarriers. In this paper, the joint optimization of frequency-domain precoding via IA, subcarrier user selection and power allocation is investigated for a cooperative three-cell OFDMA system to maximize the downlink throughput. Numerical results for a simplified symmetric channel setup reveal that the IA-based scheme achieves notable throughput gains over the traditional scheme only when the inter-cell interference link has a comparable strength as the direct link, and the receiver SNR is sufficiently large. Motivated by this observation, a practical hybrid scheme is proposed for cellular systems with heterogenous channel conditions, where the total spectrum is divided into two subbands, over which the IAbased scheme and the traditional scheme are applied for resource allocation to users located in the cell-intersection region and cellnon- intersection region, respectively. It is shown that this hybrid resource allocation scheme flexibly exploits the downlink IA gains for OFDMA-based cellular systems.Comment: 5 pages, 5 figures, GC2011 conferenc

    Secrecy Sum-Rates for Multi-User MIMO Regularized Channel Inversion Precoding

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    In this paper, we propose a linear precoder for the downlink of a multi-user MIMO system with multiple users that potentially act as eavesdroppers. The proposed precoder is based on regularized channel inversion (RCI) with a regularization parameter α\alpha and power allocation vector chosen in such a way that the achievable secrecy sum-rate is maximized. We consider the worst-case scenario for the multi-user MIMO system, where the transmitter assumes users cooperate to eavesdrop on other users. We derive the achievable secrecy sum-rate and obtain the closed-form expression for the optimal regularization parameter αLS\alpha_{\mathrm{LS}} of the precoder using large-system analysis. We show that the RCI precoder with αLS\alpha_{\mathrm{LS}} outperforms several other linear precoding schemes, and it achieves a secrecy sum-rate that has same scaling factor as the sum-rate achieved by the optimum RCI precoder without secrecy requirements. We propose a power allocation algorithm to maximize the secrecy sum-rate for fixed α\alpha. We then extend our algorithm to maximize the secrecy sum-rate by jointly optimizing α\alpha and the power allocation vector. The jointly optimized precoder outperforms RCI with αLS\alpha_{\mathrm{LS}} and equal power allocation by up to 20 percent at practical values of the signal-to-noise ratio and for 4 users and 4 transmit antennas.Comment: IEEE Transactions on Communications, accepted for publicatio
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