MIMO detection
Được đăng lên bởi
leduonglongdt5bk
Số trang: 49 trang

Lượt xem: 298 lần

Lượt tải: 0 lần
THE WORK HAS BEEN SUBMITTED TO IEEE COMMUNICATIONS SURVEYS & TUTORIALS, 2015. 1 Fifty Years of MIMO Detection: The Road to LargeScale MIMOs Shaoshi Yang, Member, IEEE and Lajos Hanzo, Fellow, IEEE Abstract—The emerging massive/largescale multipleinput multipleoutput (LSMIMO) systems that rely on very large antenna arrays have become a hot topic of wireless communications. Compared to multiantenna aided systems being built at the time of writing, such as the longterm evolution (LTE) based fourth generation (4G) mobile communication system which allows for up to eight antenna elements at the base station (BS), the LSMIMO system entails an unprecedented number of antennas, say 100 or more, at the BS. The huge leap in the number of BS antennas opens the door to a new research field in communication theory, propagation and electronics, where random matrix theory begins to play a dominant role. Interestingly, LSMIMOs also constitute a perfect example of one of the key philosophical principles of the Hegelian Dialectics, namely that “quantitative change leads to qualitative change”. In this treatise, we provide a recital on the historic heritages and novel challenges facing LSMIMOs from a detection perspective. Firstly, we highlight the fundamentals of MIMO detection, including the nature of cochannel interference (CCI), the generality of the MIMO detection problem, the received signal models of both linear memoryless MIMO channels and dispersive MIMO channels exhibiting memory, as well as the complexvalued versus realvalued MIMO system models. Then, an extensive review of the representative MIMO detection methods conceived during the past fifty years (19652015) is presented, and relevant insights as well as lessons are inferred for the sake of designing complexityscalable MIMO detection algorithms that are potentially applicable to LSMIMO systems. Furthermore, we divide the LSMIMO systems into two types, and elaborate on the distinct detection strategies suitable for each of them. The typeI LSMIMO corresponds to the case where the number of active users is much smaller than the number of BS antennas, which is currently the mainstream definition of LSMIMO. The typeII LSMIMO corresponds to the case where the number of active users is comparable to the number of BS antennas. Finally, we discuss the applicability of existing MIMO detection algorithms in LSMIMO systems, and review some of the recent advances in LSMIMO detection. Index Terms—C...
THE WORK HAS BEEN SUBMITTED TO IEEE COMMUNICATIONS SURVEYS & TUTORIALS, 2015. 1
Fifty Years of MIMO Detection: The Road to
LargeScale MIMOs
Shaoshi Yang, Member, IEEE and Lajos Hanzo, Fellow, IEEE
Abstract—The emerging massive/largescale multipleinput
multipleoutput (LSMIMO) systems that rely on very large an
tenna arrays have become a hot topic of wireless communications.
Compared to multiantenna aided systems being built at the time
of writing, such as the longterm evolution (LTE) based fourth
generation (4G) mobile communication system which allows for
up to eight antenna elements at the base station (BS), the LS
MIMO system entails an unprecedented number of antennas,
say 100 or more, at the BS. The huge leap in the number of BS
antennas opens the door to a new research ﬁeld in communication
theory, propagation and electronics, where random matrix theory
begins to play a dominant role. Interestingly, LSMIMOs also
constitute a perfect example of one of the key philosophical
principles of the Hegelian Dialectics, namely that “quantitative
change leads to qualitative change”.
In this treatise, we provide a recital on the historic her
itages and novel challenges facing LSMIMOs from a detection
perspective. Firstly, we highlight the fundamentals of MIMO
detection, including the nature of cochannel interference (CCI),
the generality of the MIMO detection problem, the received signal
models of both linear memoryless MIMO channels and dispersive
MIMO channels exhibiting memory, as well as the complex
valued versus realvalued MIMO system models. Then, an
extensive review of the representative MIMO detection methods
conceived during the past ﬁfty years (19652015) is presented, and
relevant insights as well as lessons are inferred for the sake of
designing complexityscalable MIMO detection algorithms that
are potentially applicable to LSMIMO systems. Furthermore,
we divide the LSMIMO systems into two types, and elaborate
on the distinct detection strategies suitable for each of them. T he
typeI LSMIMO corresponds to the case where the number of
active users is much smaller than the number of BS antennas,
which is currently the mainstream deﬁnition of LSMIMO. The
typeII LSMIMO corresponds to the case where the number
of active users is comparable to the number of BS antennas.
Finally, we discuss the applicability of exist ing MIMO detection
algorithms in LSMIMO systems, and review some of the recent
advances in LSMIMO detection.
Index Terms—Cochannel interference (CCI), equalization,
largescale/massive MIMO, multiuser detection, MIMO detec
tion.
GLOSSARY
3G third generation.
4G fourth generation.
5G ﬁfth generation.
ACPDA approximate complexvalued probabilistic data association.
The ﬁnancial support of the Research Councils UK (RCUK) under the
IndiaUK Advanced Technology Center (IUATC), of the EU under the
auspices of the Concerto project, and of the European Research Councils
Advanced Fellow Grant is gratefully acknowledged.
The authors are with the School of Electronics and Computer Science,
University of Southampton, Southampton, SO17 1BJ, UK (email: {lh,
shaoshi.yang}@ecs.soton.ac.uk).
ACO ant colony optimization.
AME asymptoticmultiuserefﬁciency.
APP a posteriori probability.
ASIC applicationspeciﬁc integrated circuit.
AWGN additive white Gaussian noise.
BALM block alternating likelihood maximization.
BCSDPR boundconstrained semideﬁnite programming relaxation.
BER biterror rate.
BIGDFE blockiterative generalized decision feedback equalizer.
BLER blockerror rate.
BP belief propagation.
BPSK binary phaseshift keying.
BS base station.
CAGR compound annual growth rate.
CCI cochannel interference.
CDM codedivision mu ltiplexing.
CDMA codedivision multipleaccess.
CLPS closest latticepoint search.
CMOS complementary metaloxide semiconductor.
CPDA complexvalued probabilistic data association.
DFD decisionfeedback detector.
DSCDMA directsequence codedivision multipleaccess.
DSNR decreasing signaltonoise ratio.
EB exabytes.
EM expectationmaximization.
EXIT extrinsic information transfer.
FCSD ﬁxedcomplexity sphere decoding/decoder.
FDM frequencydivision multiplexing.
FDMA frequencydivision multipleaccess.
FEC forwarderrorcorrection.
FER frameerror rate.
FHCDMA frequencyhopped codedivision multipleaccess.
FIR ﬁnite impulse response.
GA genetic algorithm.
GSNR greatest signaltonoise ratio.
HNN Hopﬁeld neural network.
IAI interantenna interference.
IC integrated circuit.
ICI interchannel interference.
IDD iterative detection and decoding.
IMSE increasing meansquare error.
ISI intersymbol interference.
JPDA joint probabilistic data association.
LAS likelihood ascent search.
LDPC lowdensity paritycheck.
LLL LenstraLenstraLov
´
asz.
LMSE least meansquare error.
LR latticereduction.
LS leastsquares.
LSMIMO largescale multipleinput multipleoutput.
LSD list sphere decoding.
LTE longterm evolution.
LTEA Long Term EvolutionAdvanced.
M2M machinetomachine.
MAI multipleaccess interference.
MAME maximum asymptoticmultiuserefﬁciency.
MAP maximum a posteriori.
MBER minimum bit error rate.
MCCDMA multicarrier codedivision multipleaccess.
MED minimum Euclidean distance.
MF matched ﬁlter.
MFB matched ﬁlter bound.
MFSK multiple frequencyshift keying.
Để xem tài liệu đầy đủ. Xin vui lòng
Đăng nhập
Nếu xem trực tuyến bị lỗi, bạn có thể tải về máy để xem.
MIMO detection

Người đăng:
leduonglongdt5bk
5
Tài liệu rất hay!
Được đăng lên bởi
dangthustony

1 giờ trước
Đúng là cái mình đang tìm. Rất hay và bổ ích. Cảm ơn bạn!
49
Vietnamese
MIMO detection
9
10
713