الگوریتم تطبیقی بر پایه حسگری فشرده جهت بهبود تخمین کانال سیستم‌های M-MIMO
محورهای موضوعی : ارتباطات بی سیم
محمدعلی عابدی
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افروز حق بین
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فربد رزازی
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1 - دانشکده مهندسی مکانیک، برق و کامپیوتر- واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران
2 - دانشکده مهندسی مکانیک، برق و کامپیوتر- واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران
3 - دانشکده مهندسی مکانیک، برق و کامپیوتر- واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران
کلید واژه: داده آموزشی موردنیاز, تخمین کانال, حسگری فشرده, تنکی مکانی, چندورودی-چندخروجی انبوه,
چکیده مقاله :
برای غلبه بر مشکل تخمین کانال در سامانه‌های چندورودی-چندخروجی انبوه (M-MIMO)، در این مقاله یک طرح تخمین کانال لینک فروسو در ارتباط دوطرفه فرکانسی (FDD) مبتنی بر حسگری فشرده ساختارمند (SCS)، برای کاهش داده آموزشی مورد نیاز پیشنهاد گردیده که توسط آن تنکی مکانی ذاتی کانال های حوزه تاخیر سامانه‌های چندورودی-چندخروجی انبوه، تقویت می شوند. به همین منظور در ابتدا پس از طرح موضوع روش های مختلف تخمین کانال و بررسی چالش‌های موجود، با پیشنهاد یک الگوریتم بر پایه الگوریتم حریصانه جستجوی تطابق متعامد (OMP)، به تخمین کانال پرداخته شده است. در این الگوریتم از همبستگی مکانی بین پاسخ ضربه کانال آنتن های مختلف فرستنده برای دقت تخمین کانال استفاده می شود. این همبستگی در زمان تاخیر یکسان مسیرهای تاخیردار تعریف شده است. این الگوریتم تنکی کانال را به صورت تطبیقی به دست می آورد که نافی فرض ایده آل کارهای پیشین مبنی بر در دست داشتن تنکی کانال است. در این صورت این الگوریتم در مواقعی که میزان دقیق تنک بودن کانال مشخص نباشد، کانال را با دقت خوبی تخمین می زند. در نهایت به ارائه شبیه سازی ها که توانایی این روش را در کاهش داده آموزشی مورد نیاز نشان می دهد، پرداخته شده است. شبیه سازی ها نشان می دهند که تخمین کانال پیشنهادی به طور قابل‌اعتمادی سطح تنکی کانال و مجموعه پشتیبان را نسبت به روش های مشابه به دست می آورد.
To overcome the problem of channel estimation in massive multiple-input multiple-output (M-MIMO) systems, in this paper we propose a downlink link channel estimation scheme in frequency-division duplex (FDD) based on structured compressive sensing to reduce the pilot required by which Intrinsic spatial sparsity of M-MIMO delay channels are amplified. For this purpose, first, after discussing the different methods of channel estimation and examining the existing challenges, we define our roadmap and propose our algorithm, in which we estimate the channel based on the greedy orthogonal matching pursuit (OMP) algorithm. In this algorithm, spatial correlation between the channel impulse response of different transmitter antennas is used for accurate channel estimation. This algorithm obtains the channel sparsity in an adaptive way, which negates the ideal assumption of the previous works that the channel sparsity is in hand. In this case, this algorithm estimates the channel with good accuracy in cases when the exact amount of channel sparsity is not known. Finally, we present simulations that demonstrate the ability of this method to reduce the required pilot. The simulations show that the proposed channel estimation reliably obtains the channel sparsity level and the support set compared to similar methods.
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