Sökning: "LS Estimator"

Hittade 3 uppsatser innehållade orden LS Estimator.

  1. 1. Pilot Contamination and Mitigation Techniques in Massive MIMO Systems

    Master-uppsats, Lunds universitet/Institutionen för elektro- och informationsteknik

    Författare :Vidit Saxena; [2014]
    Nyckelord :Multicell Systems; Massive MIMO; Pilot Contamination; LTE; Power Control; Resource Allocation; Channel Estimation; Precoding; Technology and Engineering;

    Sammanfattning : A multi-antenna base station (BS) can spatially multiplex a few terminals over the same bandwidth, a technique known as multi-user, multiple-input multiple-output (MU-MIMO). A new idea in cellular MU-MIMO is the use of a large excess of BS antennas to serve several single-antenna terminals simultaneously. LÄS MER

  2. 2. SNR Estimation for Preamble-based Wireless OFDM Systems using Extended Kalman Filter

    Master-uppsats, Blekinge Tekniska Högskola/Sektionen för ingenjörsvetenskap; Blekinge Tekniska Högskola/Sektionen för ingenjörsvetenskap

    Författare :Shravan Kumar Parsi; Sridhar Basa; [2011]
    Nyckelord :Extended Kalman Filter; Fading channels; Least squares; OFDM; SNR;

    Sammanfattning : In Orthogonal Frequency Division Multiplexing (OFDM) systems, robustness in frequency selective channels is achieved using adaptable transmission parameters. To reckon these parameters, knowledge of Signal to Noise Ratio (SNR) estimates obtained by channel state information is essential. LÄS MER

  3. 3. Low Complexity Channel Estimation for OFDM Systems Based on LS and MMSE Estimators’

    Master-uppsats, Blekinge Tekniska Högskola/Sektionen för ingenjörsvetenskap; Blekinge Tekniska Högskola/Sektionen för ingenjörsvetenskap

    Författare :Md. Jobayer Alam; Shaha Mohammed Goni Abed Sujan; [2010]
    Nyckelord :Channel Estimation; OFDM; LS Estimator; MMSE Estimator; SLS estimator; Complexity calculation;

    Sammanfattning : In this paper we investigate the block-type pilot channel estimation for orthogonal frequency-division multiplexing (OFDM) systems. The estimation is based on the minimum mean square error (MMSE) estimator and the least square (LS) estimator. We derive the MMSE and LS estimators’ architecture and investigate their performances. LÄS MER

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