36 research outputs found

    The Distributed MIMO Scenario: Can Ideal ADCs Be Replaced by Low-resolution ADCs?

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    This letter considers the architecture of distributed antenna system, which is made up of a massive number of single-antenna remote radio heads (RRHs), some with full-resolution but others with low-resolution analog-to-digital converter (ADC) receivers. This architecture is greatly motivated by its high energy efficiency and low-cost implementation. We derive the worst-case uplink spectral efficiency (SE) of the system assuming a frequency-flat channel and maximum-ratio combining (MRC), and reveal that the SE increases as the number of quantization bits for the low-resolution ADCs increases, and the SE converges as the number of RRHs with low-resolution ADCs grows. Our results furthermore demonstrate that a great improvement can be obtained by adding a majority of RRHs with low-resolution ADC receivers, if sufficient quantization precision and an acceptable proportion of high-to-low resolution RRHs are used.Comment: 4 pages, to be published in IEEE Wireless Communications Letter

    Multi-user mmWave MIMO channel estimation with hybrid Beamforming over frequency selective fading channels

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    In multi-user millimeter wave (mmWave) multiple input multiple output (MIMO) systems, obtaining accurate information/knowledge regarding the channel state is crucial to achieving multi-user interference cancellation and reliable beamforming (BF)-to compensate for severe path loss. This knowledge is nonetheless very challenging to acquire in practice since large antenna arrays experience a low signal-to-noise ratio (SNR) before BF. In this paper, a multi-user channel estimation (CE) scheme namely generalized-block compressed sampling matching pursuit (G-BCoSaMP), is proposed for multi-user mmWave MIMO systems over frequency selective fading channels. This scheme exploits the cluster-structured sparsity in the angular and delay domain of mmWave channels determined by the actual spatial frequencies of each path. As the corresponding spatial frequencies of multi-user mmWave MIMO systems with Hybrid BF often fall between the discrete Fourier transform (DFT) bins due to the continuous Angle of Arrival (AoA)/Angle of Departure (AoD), the proposed G-BCoSaMP algorithm can address the resulting power leakage problem. Simulation results show that the proposed algorithm is effective and offer a better CE performance in terms of MSE when compared to the generalized block orthogonal matching pursuit (G-BOMP) algorithm that does not possess a pruning step

    A Genetic Algorithm-based Beamforming Approach for Delay-constrained Networks

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    In this paper, we study the performance of initial access beamforming schemes in the cases with large but finite number of transmit antennas and users. Particularly, we develop an efficient beamforming scheme using genetic algorithms. Moreover, taking the millimeter wave communication characteristics and different metrics into account, we investigate the effect of various parameters such as number of antennas/receivers, beamforming resolution as well as hardware impairments on the system performance. As shown, our proposed algorithm is generic in the sense that it can be effectively applied with different channel models, metrics and beamforming methods. Also, our results indicate that the proposed scheme can reach (almost) the same end-to-end throughput as the exhaustive search-based optimal approach with considerably less implementation complexity

    A beamforming comparative study of least mean square, genetic algorithm and grey wolf optimization algorithms for multipath smart antenna system

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    Multipath environment is a limitation fact in optimized usage of wireless networks. Using smart antenna and beamforming algorithms contributed to that subscribers get a higher-gain signal and better directivity as well as reduce the consumed power for users and the mobile base stations by adjusting the appropriate weights for each element in the antenna array that leads to reducing interference anddirecting the main beam to wanted user. In this paper, the performance of three of beamforming algorithms in multipath environment in terms of directivity and side lobe level reduction has been studied and compared, which are least mean square (LMS), genetic algorithm (GA) and grey wolf optimization (GWO) technique. The simulation result appears that LMS algorithm aids us to get the best directivity followed by the GWO, and we may get most sidelobe level reduction by using the GA algorithm, followed by LMS algorithm in second rank. 

    A wireless precoding technique for millimetre-wave MIMO system based on SIC-MMSE

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    A communication method is proposed using Minimum Mean Square Error (MMSE) precoding and Successive Interference Cancellation (SIC) technique for millimetre-wave multiple-input multiple-output (mm-Wave MIMO) based wireless communication system. The mm-Wave MIMO technology for wireless communication system is the base potential technology for its high data transfer rate followed by data instruction and low power consumption compared to Long-Term Evolution (LTE). The mm-Wave system is already available in indoor hotspot and Wi-Fi backhaul for its high bandwidth availability and potential lead to rate of numerous Gbps/user. But, in mobile wireless communication system this technique is lagging because the channel faces relative orthogonal coordination and multiple node detection problems while rapid movement of nodes (transmitter and receiver) occur. To improve the conventional mm-wave MIMO nodal detection and coordination performance, the system processes data using symbolized error vector technique for linearization. Then the MMSE precoding detection technique improves the link strength by constantly fitting the channel coefficients based on number of independent service antennas (M), Signal to Noise Ratio (SNR), Channel Matrix (CM) and mean square errors (MSE). To maintain sequentially encoded user data connectivity and to overcome data loss, SIC method is used in combination with MMSE. MATLAB was used to validate the proposed system performance

    A Random Matrix Model for mmWave MIMO Systems

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    Random matrices are nowadays classical tools for modeling multiantenna wireless channels. Scattering phenomena typical of cellular frequencies and channel reciprocity features led to the adoption of matrices sampled either from the Gaussian Unitary Ensemble (GUE) or from more general Polynomial Ensembles (PE). Such matrices can be used to model the random impairments of the radio channel on the transmitted signal over a wireless link whose transmitter and receiver are both equipped with antenna arrays. The exploitation of the millimeter-wave (mmWave) frequency band, planned for 5G and beyond mobile networks, prevents the use of GUE and PE elements as candidate models for channel matrices. This is mainly due to the lack of scattering richness compared to microwave-based transmissions. In this work, we propose to model mmWave Multi-Input–MultiOutput (MIMO) systems via products of random Vandermonde matrices. We illustrate the physical motivation of our model selection, discuss the meaning of the parameters and their impact on the spectral properties of the random matrix at hand, and provide both a list of results of immediate use for performance analysis of mmWave MIMO systems, as well as a list of open problems in the field

    Random-Phase Beamforming for Initial Access in Millimeter-Wave Cellular Networks

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    The utilization of the millimeter-wave frequency band (mm-wave) in the fifth generation (5G) of mobile communication is a highly-debated current topic. Mm-wave MIMO systems will use arrays with large number of antennas at the transmitter and the receiver, implemented on a relatively small area. With the inherent high directivity of these arrays, algorithms to help the user equipment find the base station and establish a communication link should be carefully designed. Towards that, we examine two beamforming schemes, namely, random-phase beamforming (RPBF) and directional beamforming (DBF), and test their impact on the Cramer-Rao lower bounds (CRB) of jointly estimating the ´ direction-of-arrival, direction-of-departure, time-of-arrival, and the complex channel gain, under the line-of-sight channel model. The results show that the application of RPBF is more appropriate in the considered scenario as it attains a lower CRB with fewer beams compared to DB.ARC Discovery Projects Grant DP14010113
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