JP2023520538A - ハードウェア障害が存在する場合のノイズの多い過負荷無線通信システムにおける離散デジタル信号回復の方法 - Google Patents
ハードウェア障害が存在する場合のノイズの多い過負荷無線通信システムにおける離散デジタル信号回復の方法 Download PDFInfo
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- H04B1/10—Means associated with receiver for limiting or suppressing noise or interference
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- H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
- H04B7/0613—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission
- H04B7/0615—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal
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Abstract
Description
欧州特許第2019/079532号明細書、題名「Method of estimating transmit Symbol Vectors in an overloaded Communication Channel」。
欧州特許第2020/082987号明細書、題名「Method for Wireless X2X Access and Receivers for Large Multidimensional Wireless Systems」。
H.Iimori、G.Abreu、D.Gonzalez G.、及びO.Gonsaによる“Joint detection in massive overloaded wireless systems via mixed-norm discrete vector decoding,”in Proc.Asilomar CSSC,Pacific Grove,USA、参照文献[11]。
H.Iimori、R.-A.Stoica、G.T.F.de Abreu、D.Gonzalez G.、A.Andrae、及びO.Gonsaによる“Discreteness-aware receivers for overloaded MIMO systems,”CoRR,vol.abs/2001.07560,2020、参照文献[12]。
De Mi、Mehrdad Dianati、Lei Zhang、Sami Muhaidat、及びRahim Tafazolliによる“Massive MIMO Performance With Imperfect Channel Reciprocity and Channel Estimation Error”IEEE TRANSACTIONS ON COMMUNICATIONS,VOL.65,NO.9,SEPTEMBER 2017。この論文では、チャネル推定と相反エラーを使用してTDDシステムでSINRを推定する方法について説明する。ここでも、信号の電力が既知である(パイロット)と仮定すると、チャネル推定エラーによるSINRの増加を測定できる。
Hwanjin Kim及びJunil Choiによる“Channel Estimation for Spatially/Temporally Correlated Massive MIMO Systems with One-Bit ADCs”arXiv:1910.13243 9 Dec 2019,1910.13243.pdf(arxiv.org)で入手可能。この論文では、リソースに制約のあるシステム(1ビットADC)のコンテキストでこれを行う方法について説明している。
Mahdi Barzegar Khalilsarai、Saeid Haghighatshoar、Xinping Yi、及びGiuseppe Caireによる“FDD Massive MIMO via UL/DL Channel Covariance Extrapolation and Active Channel Sparsification”arXiv:1803.05754v2[cs.IT]24 Aug 2018;1803.05754.pdf(arxiv.org)で入手可能。
G.E.Prescott、J.L.Hammond、及びD.R.Hertlingによる“Adaptive estimation of transmission distortion in a digital communications channel,”in IEEE Transactions on Communications,vol.36,no.9,pp.1070-1073,Sept.1988,doi:10.1109/26.7519。
S=x+w (2)
であり、ここで、wは、w~CN(0,η・diag(xHx))としてモデル化される加法的ハードウェア歪みベクトルであり、ηはRFチェーンの品質によって特徴付けられるRF歪みレベルパラメータを示す。
Claims (11)
- 複素係数のチャネル行列によって特徴付けられる、ハードウェア障害の存在下でのノイズの多い過負荷の無線通信システムにおける離散デジタル信号回復のコンピュータ実装再構成方法であって、
信号検出器(212)によってチャネル(208)から前記信号を受信することと、
ハードウェア障害パラメータηの推定が前記受信機で行われることと、
ノイズ電力の推定がノイズ電力推定器(210)によって行われることと、
前記検出された信号、ハードウェア障害パラメータη、及びノイズ電力推定を、送信されたシンボルを推定する復号器(214)に転送することと、
を含み、
前記復号器(214)の前記推定が、おそらく送信された可能性があるシンボルを生成して、それがデマッパー(216)に転送され、前記デマッパー(216)は、前記推定された送信信号に対応するビット推定及び前記対応する推定されたシンボルを、さらなる処理のためにマイクロプロセッサ(218)に出力する、
コンピュータ実装再構成方法。 - チャネル相関は、この相関を捕捉する共分散行列内に組み込まれるハードウェア障害(η)に起因すると仮定される、請求項1に記載の方法。
- ハードウェア障害(η)の影響を最小化することは、復号器(214)によって使用される目的関数内の前記チャネル相関を補償することによって行われる、請求項1又は2に記載の方法。
- 分数計画法アルゴリズムは、前記第1の関数のグローバル最小値よりも低い前記第3の関数の値を見つけることを目標とする、請求項4に記載の方法。
- 前記第1の関数は、前記チャネル相関効果を含む前記受信信号のベクトルを中心とするユークリッド距離関数である、請求項4に記載の方法。
- 前記第2の関数は、前記推定されたノイズ電力と送信信号電力との積である、請求項4に記載の方法。
- 前記第3の関数は、l0ノルムに基づくか、又は厳密に近似する関数である、請求項4に記載の方法。
- プロセッサ、揮発性及び/又は不揮発性メモリ、通信チャネル(208)において信号を受信するように適合される少なくとも1つのインターフェースを有する通信システムの受信機(R)であって、前記不揮発性メモリが、マイクロプロセッサによる実行時に請求項1~4の1つ又は複数の方法を実施するように前記受信機を構成するコンピュータプログラム命令を記憶する、受信機(R)。
- コンピュータ上での実行時に前記コンピュータに請求項1~8のいずれか一項に記載の方法を実行させるコンピュータ実行可能命令を含む、コンピュータプログラム製品。
- 請求項10のコンピュータプログラム製品を記憶及び/又は送信する、コンピュータ可読媒体。
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