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    5G NR-๋ฐด๋“œ ๋ฌด์„  ์ฃผํŒŒ์ˆ˜ ์†ก์ˆ˜์‹ ๊ธฐ์˜ ๊ฒ€์ฆ์„ ์œ„ํ•œ ๋ชจ๋ธ๋ง ๋ฐฉ๋ฒ•

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ์ „๊ธฐยท์ •๋ณด๊ณตํ•™๋ถ€, 2021.8. ๊น€์žฌํ•˜.๋„๋ž˜ํ•œ ์ดˆ์—ฐ๊ฒฐ์‹œ๋Œ€์—์„œ๋Š” ์Šค๋งˆํŠธํฐ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ๋‹ค์–‘ํ•œ ์‚ฌ๋ฌผ ์ธํ„ฐ๋„ท ๋””๋ฐ”์ด์Šค๋“ค์ด 5์„ธ๋Œ€ ์ด๋™ํ†ต์‹  ์‹œ์Šคํ…œ์„ ํ™œ์šฉํ•˜๋ฉด์„œ, ๋Š˜์–ด๋‚œ ๋ฐ์ดํ„ฐ๋Ÿ‰๊ณผ ํŠธ๋ž˜ํ”ฝ์„ ๊ฐ๋‹นํ•˜๊ธฐ ์œ„ํ•ด ๋ฐ€๋ฆฌ๋ฏธํ„ฐํŒŒ ๋Œ€์—ญ์˜ ์‚ฌ์šฉ์ด ํ•„์ˆ˜์ ์ผ ๊ฒƒ์ด๋‹ค. ์‹œ์Šคํ…œ์ด ๋ณด๋‹ค ๋Œ€์šฉ๋Ÿ‰ํ™” ๊ทธ๋ฆฌ๊ณ  ๊ด‘๋Œ€์—ญํ™” ๋จ์— ๋”ฐ๋ผ, ํ†ต์‹  ๊ทœ์•ฝ์„ ๋งŒ์กฑ์‹œํ‚ค๊ธฐ ์œ„ํ•ด, ์ ์ฐจ ๊ฑฐ๋Œ€ํ•œ ๋””์ง€ํ„ธ ์บ˜๋ฆฌ๋ธŒ๋ ˆ์ด์…˜ ๋ฐ ์‹ ํ˜ธ์ฒ˜๋ฆฌ ๋กœ์ง์ด, ๋ฌด์„  ํ†ต์‹  ์ „๋‹จ๋ถ€ ์นฉ์— ํ•จ๊ป˜ ์ง‘์ ๋˜๊ณ  ์žˆ๋‹ค. ๋”ฐ๋ผ์„œ ๋ฉ€ํ‹ฐ-๋„๋ฉ”์ธ์˜ ์‹ ํ˜ธ(์•„๋‚ ๋กœ๊ทธ/๋””์ง€ํ„ธ/๋ฌด์„ ํ†ต์‹  ์‹ ํ˜ธ)๊ฐ€ ๋ณต์žกํ•˜๊ฒŒ ํ˜ผ์„ฑ๋œ ๋ฌด์„ ํ†ต์‹  ์ง‘์ ํšŒ๋กœ ์นฉ์„, ์งง์€ ๊ฐœ๋ฐœ ๊ธฐ๊ฐ„ ๋™์•ˆ ์ถฉ๋ถ„ํžˆ ๊ฒ€์ฆํ•˜๊ธฐ์—” ์–ด๋ ค์›€์ด ๋”ฐ๋ฅธ๋‹ค. ์ผ๋ฐ˜์ ์œผ๋กœ ํ˜ผ์„ฑ ์‹ ํ˜ธ ์‹œ์Šคํ…œ์„ ๊ฒ€์ฆํ•˜๊ธฐ ์œ„ํ•ด์„œ๋Š”, ํ•˜์œ„ ์‹œ์Šคํ…œ์„ ๋ชจ๋‘ ํฌํ•จํ•ด์„œ ์‹œ๊ฐ„ ๋„๋ฉ”์ธ์˜ ์‹œ๋ฎฌ๋ ˆ์ด์…˜์„ ์ˆ˜ํ–‰ํ•ด์•ผ ํ•˜๋Š”๋ฐ, ์ด๋ฅผ ์œ„ํ•œ ์ŠคํŒŒ์ด์Šค์™€ ์ŠคํŒŒ์ด์Šค-ํ•˜๋“œ์›จ์–ด ๊ธฐ์ˆ  ์–ธ์–ด์˜ co-์‹œ๋ฎฌ๋ ˆ์ด์…˜์€ ์ง€๋‚˜์น˜๊ฒŒ ๋Š๋ฆฌ๋‹ค๋Š” ํ•œ๊ณ„๊ฐ€ ์žˆ๊ธฐ ๋•Œ๋ฌธ์ด๋‹ค. ๋”ฐ๋ผ์„œ, ๋ฉ€ํ‹ฐ-๋„๋ฉ”์ธ์˜ ์‹ ํ˜ธ๋ฅผ ๋น ๋ฅด๊ณ  ์ •ํ™•ํ•˜๊ฒŒ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๊ฐ€๋Šฅํ•˜๊ฒŒ ํ•˜๋Š” ๋ชจ๋ธ๋ง ๋ฐฉ๋ฒ•๊ณผ, ๋‹ค์–‘ํ•œ ์‹œ๋‚˜๋ฆฌ์˜ค์˜ ๊ฒ€์ฆ ์™„์„ฑ๋„๋ฅผ ํ–ฅ์ƒ์‹œ์ผœ์ค„ ์žˆ๋Š” ๊ฒ€์ฆ ๊ธฐ์ˆ ์ด ๋ชจ๋‘ ์š”๊ตฌ๋œ๋‹ค. ํ˜ผ์„ฑ ์‹œ์Šคํ…œ์„ ๊ฒ€์ฆํ•˜๊ธฐ ์œ„ํ•ด์„œ๋Š”, ์•„๋‚ ๋กœ๊ทธ์™€ ๋ฌด์„  ํ†ต์‹  ๋ธ”๋ก๋“ค์„ ์‹œ์Šคํ…œ ๋ฒ ๋ฆด๋กœ๊ทธ ์ƒ์—์„œ ๊ตฌํ˜„๋œ ํ•จ์ˆ˜์  ๋ชจ๋ธ๋กœ ๋Œ€์ฒดํ•˜๊ณ , ๋””์ง€ํ„ธ ๋ธ”๋ก๋“ค๊ณผ ํ•จ๊ป˜ ํ•˜๋‚˜์˜ ๋””์ง€ํ„ธ ํ”Œ๋žซํผ์—์„œ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ํ•˜๋Š” ๊ฒƒ์ด ํšจ๊ณผ์ ์ด๋‹ค. ์‹ค์ œ ์„ค๊ณ„ํ•  ๋•Œ, ๋ฌธ์ œ๊ฐ€ ๋˜๋Š” ๋Œ€๋ถ€๋ถ„์˜ ์—๋Ÿฌ๋“ค์€, ์—ฐ๊ฒฐ ์˜ค๋ฅ˜, ๋ถ€ํ˜ธ ์˜ค๋ฅ˜, ์‹ ํ˜ธ ์ˆœ์„œ ์˜ค๋ฅ˜, ํ˜น์€ ์ž˜๋ชป๋œ ํŒŒ์›Œ ๋„๋ฉ”์ธ๊ณผ์˜ ์—ฐ๊ฒฐ๊ณผ ๊ฐ™์ด ์‚ฌ์†Œํ•œ ์˜ค๋ฅ˜๋“ค์ด๋‹ค. ์ด๋Ÿฌํ•œ ์˜ค๋ฅ˜๋ฅผ ์ฐพ๊ธฐ ์œ„ํ•ด, ์˜ค๋ž˜ ๊ฑธ๋ฆฌ๋Š” ํŠธ๋žœ์ง€์Šคํ„ฐ-๋ ˆ๋ฒจ์˜ ์‹œ๋ฎฌ๋ ˆ์ด์…˜์„ ์ˆ˜ํ–‰ํ•˜๊ธฐ๋ณด๋‹ค๋Š”, ์•„๋‚ ๋กœ๊ทธ ์ŠคํŒŒ์ด์Šค ๋ชจ๋ธ๋“ค์„ ์‹œ์Šคํ…œ ๋ฒ ๋ฆด๋กœ๊ทธ ๋ชจ๋ธ๋“ค๋กœ ๋Œ€์ฒดํ•˜๊ณ , ๋ณด๋‹ค ๋‹ค์–‘ํ•œ ์‹œ๋‚˜๋ฆฌ์˜ค๋ฅผ ๋น ๋ฅด๊ฒŒ ๊ฒ€์ฆํ•˜๋Š” ๋ฐฉ๋ฒ•์ด ๊ฒ€์ฆ ์™„์„ฑ๋„๋ฅผ ํ–ฅ์ƒ์‹œํ‚ค๋Š”๋ฐ ์ ํ•ฉํ•˜๋‹ค. ๊ทธ๋Ÿผ์—๋„, ์ง€๋‚˜์น˜๊ฒŒ ๋‹จ์ˆœํ•œ ์„ ํ˜• ๋ชจ๋ธ์ด๋‚˜, ์ค‘์š”ํ•œ ํšŒ๋กœ ํŠน์„ฑ์ด ๋น ์ง„ ๋ชจ๋ธ๋กœ๋Š” ์›ํ•˜๋Š” ์ˆ˜์ค€์˜ ๊ฒ€์ฆ์ด ๋ถˆ๊ฐ€๋Šฅํ•  ์ˆ˜ ์žˆ๋‹ค. ์˜ˆ๋ฅผ ๋“ค์–ด, ์ง์ ‘ ๋ณ€์กฐ ๊ตฌ์กฐ์˜ ๋ฌด์„ ํ†ต์‹  ์†ก์ˆ˜์‹ ๊ธฐ์—์„œ ๋ฐœ์ƒํ•˜๋Š” ๋น„์ด์ƒ ํšจ๊ณผ, ์ €์ „๋ ฅ ๋™์ž‘์„ ํ•˜๋ฉด์„œ ๋ฐœ์ƒํ•˜๋Š” ๋น„์„ ํ˜• ํšจ๊ณผ, ๊ทธ๋ฆฌ๊ณ  ํ”ํžˆ ๋ฉ”๋ชจ๋ฆฌ ํšจ๊ณผ๋Š” ๋ชจ๋ธ์— ํšจ๊ณผ๋ฅผ ์ถฉ๋ถ„ํžˆ ๋ฐ˜์˜ํ•ด ์ฃผ์–ด์•ผ๋งŒ, ์ฃผํŒŒ์ˆ˜ ๋„๋ฉ”์ธ์—์„œ์˜ ๊ฒ€์ฆ, ์„ฑ๋Šฅ ์˜ˆ์ธก ๋“ฑ์˜ ๊ฒ€์ฆ์„ ์˜๋ฏธ ์žˆ๊ฒŒ ์ˆ˜ํ–‰ํ•  ์ˆ˜ ์žˆ๋‹ค. ๋ฌธ์ œ๋Š” ๋น„์„ ํ˜• ์‹œ์Šคํ…œ์€ ํ›จ์”ฌ ๋ณต์žกํ•œ ์‹์œผ๋กœ ํ‘œํ˜„๋˜๋ฉฐ, ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ์‹œ ์—ฐ์‚ฐ๋Ÿ‰๋„ ํฌ๊ฒŒ ๋Š˜์–ด๋‚˜๊ธฐ ๋•Œ๋ฌธ์—, ๋น„์„ ํ˜• ๋ชจ๋ธ์„ ๋งŒ๋“ค๊ณ  ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ํ•˜๊ธฐ๊ฐ€ ์‰ฝ์ง€ ์•Š๋‹ค๋Š” ๊ฒƒ์ด๋‹ค. ๋”ฐ๋ผ์„œ ๋ชจ๋ธ์ด ๋น„์ด์ƒ์„ฑ๋“ค์„ ์ถฉ๋ถ„ํžˆ ๋ฐ˜์˜ํ•˜๋ฉด์„œ๋„ ํšจ๊ณผ์ ์ธ ๊ฒ€์ฆ์„ ๊ฐ€๋Šฅํ•˜๊ฒŒ ํ•˜๋Š” ๋ชจ๋ธ๋ง/์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๋ฐฉ๋ฒ• ์—ญ์‹œ ์š”๊ตฌ๋œ๋‹ค. ๋ณธ ํ•™์œ„ ๋…ผ๋ฌธ์—์„œ๋Š”, ๋ฌด์„ ํ†ต์‹  ์†ก์ˆ˜์‹ ๊ธฐ ์ง‘์ ํšŒ๋กœ ์ „์ฒด์˜ ๋ชจ์‚ฌ ๋ชจ๋ธ์„ ์ œ์•ˆํ•œ๋‹ค. ๋ชจ๋ธ์€ ๋ˆ„์„ค ์‹ ํ˜ธ์™€ ์‹ ํ˜ธ ๊ฐ„ ๋ถˆ์ผ์น˜์— ์˜ํ•œ ๋น„-์ด์ƒ์ ์ธ ํšจ๊ณผ๋ฅผ ์—‘์Šค๋ชจ๋ธ์˜ ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ํ™œ์šฉํ•ด ๋ฐ˜์˜ํ•˜์˜€๊ณ , ๋น„์„ ํ˜•์„ฑ๊ณผ ๋ฉ”๋ชจ๋ฆฌ ํšจ๊ณผ๋ฅผ ๋ณผํ…Œ๋ผ-์„ญ๋™๋ฒ•์„ ํ™œ์šฉํ•ด ๋ฐ˜์˜ํ•˜์˜€๋‹ค. ์ œ์•ˆํ•˜๋Š” ๋ชจ๋ธ์€ ๋‹ค์–‘ํ•œ ์ฃผํŒŒ์ˆ˜ ๋Œ€์—ญ๊ณผ ๋™์ž‘ ๋ชจ๋“œ๋ฅผ ๊ฒ€์ฆํ•˜๋Š”๋ฐ, ๊ธฐ์กด ๋“ฑ๊ฐ€ ๋ฒ ์ด์Šค๋ฐด๋“œ ๋ชจ๋ธ๋ณด๋‹ค 30~1800๋ฐฐ ๋น ๋ฅด๊ฒŒ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ํ•  ์ˆ˜ ์žˆ์—ˆ๊ณ , ๋น„์ด์ƒ ํšจ๊ณผ์— ๋Œ€ํ•ด, ํ†ต์‹  ์„ฑ๋Šฅ๋“ค(์‹ฌ๋ณผ์˜ ์˜ค๋ฅ˜ ๋ฒกํ„ฐ์˜ ํฌ๊ธฐ, ์ธ์ ‘ ์ฑ„๋„์˜ ํŒŒ์›Œ ๊ทธ๋ฆฌ๊ณ  ๋น„ํŠธ ์—๋Ÿฌ)์„ ํ‰๊ฐ€ ๊ฐ€๋Šฅํ–ˆ๋‹ค. ๋‚˜์•„๊ฐ€, ์•„๋‚ ๋กœ๊ทธ ๊ฒ€์‚ฌ๊ธฐ๋ฅผ ํ™œ์šฉํ•œ ๊ธฐ๋Šฅ ๊ฒ€์ฆ๋ฒ•๊ณผ ๋ชจ๋ธ ํŒŒ๋ผ๋ฏธํ„ฐ ์ปค๋ฒ„๋ฆฌ์ง€ ๋ถ„์„๋ฒ•์„ ์ ์šฉํ•˜์—ฌ, ์‹œ์Šคํ…œ-๋ ˆ๋ฒจ ๊ฒ€์ฆ์˜ ์™„์„ฑ๋„๋ฅผ ํ–ฅ์ƒ์‹œ์ผฐ๋‹ค. ๋ฌด์„ ํ†ต์‹  ์ง‘์ ํšŒ๋กœ ๋ชจ๋ธ์— ๋‹ค์–‘ํ•œ ๋””์ž์ธ/ํŒŒ๋ผ๋ฏธํ„ฐ ์˜ค๋ฅ˜๋ฅผ ์ฃผ์ž…ํ•˜๊ณ , ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๋™์•ˆ ๊ฒ€์‚ฌ๊ธฐ๊ฐ€ ์ฐพ์€ ์—๋Ÿฌ์˜ ๊ฐœ์ˆ˜์™€ ์ปค๋ฒ„๋ฆฌ์ง€ ๊ฒฐ๊ณผ๋ฅผ ์‹คํ—˜์ ์œผ๋กœ ๋ณด์˜€๋‹ค.In mobile RF transceiver systems, the large number of digital circuits employed to compensate or calibrate the non-idealities of the RF circuits call for models that can work within the digital verification platform, such as SystemVerilog. While baseband-equivalent real-number models (RNMs) are the current state-of-the-art for modeling RF transceivers in SystemVerilog, their simulation speeds and accuracy are not adequate predicting performance degradation. Since, its signals can only model the frequency components near the carrier frequency but not the DC offsets or high-order harmonic effects arising due to nonlinearities. Therefore, the growing impacts of nonlinearities call for nonlinear modeling of their key components to predict the overall system's performance. This dissertation presents the models for a multi-standard, direct-conversion RF transceiver for evaluating its system-level performance and verifying its digital controllers. Also, this work demonstrates the Volterra series model for the nonlinear analysis of a low-noise amplifier circuit in SystemVerilog, leveraging the functional expression and event-driven simulation capability of XMODEL. The simulation results indicate that the presented models, including the digital configuration/calibration logic for the 5G sub-6GHz-band and mmWave-band transceiver, can deliver 30โ€“1800ร— higher speeds than the baseband-equivalent RNMs while estimating the quadrature amplitude modulation signal constellation and error vector magnitude in the presence of non-idealities such as nonlinearities, DC offsets, and I/Q imbalances. In addition, it implements functionality checkers and parameter coverage analysis to advance the completeness of system-level verification of the RF transceivers model.Chapter 1. Introduction 1 1.1 Design and Verification Flow . 1.2 5G NR Band RF Transceiver IC . 1.3 Baseband-Equivalent and Passband Modeling . 1.4 Thesis Organization . Chapter 2. Modeling and Simulation of RF Transceiver 11 2.1 Direct Conversion RF Transceiver . 2.2 Proposed Transceiver Models . 2.3 System and Simulation Performance . Chapter 3. Nonlinear RF System Modeling 28 3.1 Volterra / Perturbation Method . 3.2 Low Noise Amplifier Example . 3.3 Nonlinearity Analysis . Chapter 4. Coverage Analysis and Functional Verification 42 4.1 Model Parameter Coverage Analysis . 4.2 Self-Checking Testbench . Chapter 5. Conclusion 54 Appendix 55 A.1 Trigonometric Equation for Non-Ideal Effects . A.2 RNM Baseband Equivalent Modeling . A.3 Parameter Coverage Analysis . A.4 List of Models . Bibliography 63 Abstract in Korean 66์„

    Living and dealing with RF impairments in communication transceivers

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    This paper provides an overview of the sources and effects of the RF impairments limiting and rendering the performance of the future wireless communication transceivers costly as well as hindering their wide-spread use in commercial products. As transmission bandwidths and carrier frequencies increase effect of these impairments worsen. This paper studies and presents analytical evaluations of the performance degradation due to the RF impairments in terms of bit-error-rate and image rejection ratio. The paper also give highlights of the various aspects of the research carried out in mitigating the effects of these impairments primarily in the digital signal processing domain at the baseband as well as providing low-complexity hardware implementations of such algorithms incorporating a number of power and area saving techniques

    I/Q imbalance mitigation for space-time block coded communication systems

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    Multiple-input multiple-output (MIMO) space-time block coded (STBC) wireless communication systems provide reliable data transmissions by exploiting the spatial diversity in fading channels. However, due to component imperfections, the in-phase/quadrature (I/Q) imbalance caused by the non-ideal matching between the relative amplitudes and phases of the I and Q branches always exists in the practical implementation of MIMO STBC communication systems. Such distortion results in a complex conjugate term of the intended signal in the time domain, hence a mirror-image term in the frequency domain, in the data structure. Consequently, I/Q imbalance increases the symbol error rate (SER) drastically in MIMO STBC or STBC MIMO orthogonal frequency division multiplexing (OFDM) communication systems, where both the signal and its complex conjugate are utilized for the information transmission, hence should be mitigated effectively. In this dissertation, the impact of I/Q imbalance in MIMO STBC systems over flat fading channels, the impact of I/Q imbalance in STBC MIMO-OFDM systems and in time- reversal STBC (TR-STBC) systems over frequency-selective fading channels are studied systematically. With regard to the MIMO STBC and the STBC MIMO-OFDM systems with I/Q imbalance, orthogonal space-time block codes (OSTBCs), quasi-orthogonal STBCs (QOSTBCs) and rotated QOSTBCs (RQOSTBCs) are studied, respectively. By exploiting the special structure of the received signal, low-complexity solutions are provided to mitigate the distortion induced by I/Q imbalance successfully. In addition, to mitigate I/Q imbalance while at the same time to exploit the multipath diversity for STBC OFDM systems over frequency-selective fading channels, a new encoding/decoing scheme for the grouped linear constellation precoded (GLCP) OFDM systems with I/Q imbalance is studied. In Chapter 1, the objectives of the research are elaborated. In Chapter 2, the various I/Q imbalance models are introduced, and the model used in this dissertation is established. In Chapter 3, the performance degradation caused by I/Q imbalance of the transceivers in MIMO STBC wireless communication systems over flat fading channels and the solutions are studied. A 2 Tx Alamouti system, a 4 Tx quasi-orthogonal STBC (QOSTBC) system, and a 4 Tx rotated QOSTBC (RQOSTBC) system with I/Q imbalance are studied in detail. By exploiting the special structure of the received signal, low-complexity solutions are proposed to mitigate I/Q imbalance successfully. Since STBCs are developed for frequency-flat fading channels, to achieve the spatial diversity in frequency-selective fading channels, MIMO-OFDM arrangements have been suggested, where STBCs are used across different antennas in conjunction with OFDM. In Chapter 4, the performance degradation caused by I/Q imbalance in STBC MIMO-OFDM wireless systems over frequency-selective fading channels and the solutions are studied. Similarly, a 2 Tx Alamouti system, a 4 Tx quasi-orthogonal STBC (QOSTBC) system, and a 4 Tx rotated QOSTBC (RQOSTBC) system with I/Q imbalance are studied in detail, and low-complexity solutions are proposed to mitigate the distortion effectively. However, OFDM systems suffer from the loss of the multipath diversity by converting frequency-selective fading channels into parallel frequency-flat fading subchannels. To exploit the multipath diversity and reduce the decoding complexity, GLCP OFDM systems with I/Q imbalance are studied. By judiciously assigning the mirror-subcarrier pair into one group, a new encoding/decoding scheme with a low-complexity is proposed to mitigate I/Q imbalance for GLCP OFDM systems in Chapter 5. Since OFDM communication systems have high peak-to-average power ratio (PAPR) problem and are sensitive to carrier frequency offset (CFO), to achieve both the spatial and multipath diversity, time-reversal STBC (TR-STBC) communication systems are introduced. In Chapter 6, the I/Q imbalance mitigating solutions in TR-STBC systems, both in the time domain and in the frequency domain, are studied

    Near-Instantaneously Adaptive HSDPA-Style OFDM Versus MC-CDMA Transceivers for WIFI, WIMAX, and Next-Generation Cellular Systems

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    Burts-by-burst (BbB) adaptive high-speed downlink packet access (HSDPA) style multicarrier systems are reviewed, identifying their most critical design aspects. These systems exhibit numerous attractive features, rendering them eminently eligible for employment in next-generation wireless systems. It is argued that BbB-adaptive or symbol-by-symbol adaptive orthogonal frequency division multiplex (OFDM) modems counteract the near instantaneous channel quality variations and hence attain an increased throughput or robustness in comparison to their fixed-mode counterparts. Although they act quite differently, various diversity techniques, such as Rake receivers and space-time block coding (STBC) are also capable of mitigating the channel quality variations in their effort to reduce the bit error ratio (BER), provided that the individual antenna elements experience independent fading. By contrast, in the presence of correlated fading imposed by shadowing or time-variant multiuser interference, the benefits of space-time coding erode and it is unrealistic to expect that a fixed-mode space-time coded system remains capable of maintaining a near-constant BER

    A low-complexity self-calibrating adaptive quadrature receiver

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    In this paper digital part of a self-calibrating quadrature-receiver is described, containing a digital calibration-engine. The blind source-separation-based calibration-engine eliminates the RF-impairments in real-time hence improving the receiver's performance without the need for test/pilot tones, trimming or use of power-hungry discrete components. Furthermore, an efficient time-multiplexed calibration-engine architecture is proposed and implemented on an FPGA utilising a reduced-range multiplier structure. The use of reduced-range multipliers results in substantial reduction of area as well as power consumption without a compromise in performance when compared with an efficiently designed general purpose multiplier. The performance of the calibration-engine does not depend on the modulation format or the constellation size of the received signal; hence it can be easily integrated into the digital signal processing paths of any receiver
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