327 research outputs found
Soft metrics and their Performance Analysis for Optimal Data Detection in the Presence of Strong Oscillator Phase Noise
In this paper, we address the classical problem of maximum-likelihood (ML)
detection of data in the presence of random phase noise. We consider a system,
where the random phase noise affecting the received signal is first compensated
by a tracker/estimator. Then the phase error and its statistics are used for
deriving the ML detector. Specifically, we derive an ML detector based on a
Gaussian assumption for the phase error probability density function (PDF).
Further without making any assumptions on the phase error PDF, we show that the
actual ML detector can be reformulated as a weighted sum of central moments of
the phase error PDF. We present a simple approximation of this new ML rule
assuming that the phase error distribution is unknown. The ML detectors derived
are also the aposteriori probabilities of the transmitted symbols, and are
referred to as soft metrics. Then, using the detector developed based on
Gaussian phase error assumption, we derive the symbol error probability (SEP)
performance and error floor analytically for arbitrary constellations. Finally
we compare SEP performance of the various detectors/metrics in this work and
those from literature for different signal constellations, phase noise
scenarios and SNR values
Channel Hardening-Exploiting Message Passing (CHEMP) Receiver in Large-Scale MIMO Systems
In this paper, we propose a MIMO receiver algorithm that exploits {\em
channel hardening} that occurs in large MIMO channels. Channel hardening refers
to the phenomenon where the off-diagonal terms of the matrix
become increasingly weaker compared to the diagonal terms as the size of the
channel gain matrix increases. Specifically, we propose a message
passing detection (MPD) algorithm which works with the real-valued matched
filtered received vector (whose signal term becomes ,
where is the transmitted vector), and uses a Gaussian approximation
on the off-diagonal terms of the matrix. We also propose a
simple estimation scheme which directly obtains an estimate of (instead of an estimate of ), which is used as an effective
channel estimate in the MPD algorithm. We refer to this receiver as the {\em
channel hardening-exploiting message passing (CHEMP)} receiver. The proposed
CHEMP receiver achieves very good performance in large-scale MIMO systems
(e.g., in systems with 16 to 128 uplink users and 128 base station antennas).
For the considered large MIMO settings, the complexity of the proposed MPD
algorithm is almost the same as or less than that of the minimum mean square
error (MMSE) detection. This is because the MPD algorithm does not need a
matrix inversion. It also achieves a significantly better performance compared
to MMSE and other message passing detection algorithms using MMSE estimate of
. We also present a convergence analysis of the proposed MPD
algorithm. Further, we design optimized irregular low density parity check
(LDPC) codes specific to the considered large MIMO channel and the CHEMP
receiver through EXIT chart matching. The LDPC codes thus obtained achieve
improved coded bit error rate performance compared to off-the-shelf irregular
LDPC codes
Impact of signaling schemes on iterative linear minimum-mean-square-error detection
In this paper, we study the iterative detection problem for a coded system with multi-ary modulation. We show that, with iterative linear minimum-mean-square-error (LMMSE) detection, superposition coded modulation (SCM) can provide performance superior to that with other traditional signaling schemes used in trellis coded modulation (TCM) and bit-interleaved coded modulation (BICM). This finding provides a useful guideline for system design considering inter-symbol interference (ISI) and other forms of interference. Simulation results are provided to illustrate the efficiency of the iterative LMMSE detection with different signaling schemes. © 2008 IEEE
Capacity-Achieving Iterative LMMSE Detection for MIMO-NOMA Systems
This paper considers a iterative Linear Minimum Mean Square Error (LMMSE)
detection for the uplink Multiuser Multiple-Input and Multiple-Output (MU-MIMO)
systems with Non-Orthogonal Multiple Access (NOMA). The iterative LMMSE
detection greatly reduces the system computational complexity by departing the
overall processing into many low-complexity distributed calculations. However,
it is generally considered to be sub-optimal and achieves relatively poor
performance. In this paper, we firstly present the matching conditions and area
theorems for the iterative detection of the MIMO-NOMA systems. Based on the
proposed matching conditions and area theorems, the achievable rate region of
the iterative LMMSE detection is analysed. We prove that by properly design the
iterative LMMSE detection, it can achieve (i) the optimal sum capacity of
MU-MIMO systems, (ii) all the maximal extreme points in the capacity region of
MU-MIMO system, and (iii) the whole capacity region of two-user MIMO systems.Comment: 6pages, 5 figures, accepted by IEEE ICC 2016, 23-27 May 2016, Kuala
Lumpur, Malaysi
EQUALISATION TECHNIQUES FOR MULTI-LEVEL DIGITAL MAGNETIC RECORDING
A large amount of research has been put into areas of signal processing, medium design,
head and servo-mechanism design and coding for conventional longitudinal as well
as perpendicular magnetic recording. This work presents some further investigation in the
signal processing and coding aspects of longitudinal and perpendicular digital magnetic
recording.
The work presented in this thesis is based upon numerical analysis using various simulation
methods. The environment used for implementation of simulation models is C/C + +
programming. Important results based upon bit error rate calculations have been documented
in this thesis.
This work presents the new designed Asymmetric Decoder (AD) which is modified to
take into account the jitter noise and shows that it has better performance than classical
BCJR decoders with the use of Error Correction Codes (ECC). In this work, a new method
of designing Generalised Partial Response (GPR) target and its equaliser has been discussed
and implemented which is based on maximising the ratio of the minimum squared
euclidean distance of the PR target to the noise penalty introduced by the Partial Response
(PR) filter. The results show that the new designed GPR targets have consistently
better performance in comparison to various GPR targets previously published.
Two methods of equalisation including the industry's standard PR, and a novel Soft-Feedback-
Equalisation (SFE) have been discussed which are complimentary to each other.
The work on SFE, which is a novelty of this work, was derived from the problem of Inter
Symbol Interference (ISI) and noise colouration in PR equalisation. This work also shows
that multi-level SFE with MAP/BCJR feedback based magnetic recording with ECC has
similar performance when compared to high density binary PR based magnetic recording
with ECC, thus documenting the benefits of multi-level magnetic recording. It has been
shown that 4-level PR based magnetic recording with ECC at half the density of binary PR
based magnetic recording has similar performance and higher packing density by a factor
of 2.
A novel technique of combining SFE and PR equalisation to achieve best ISI cancellation
in a iterative fashion has been discussed. A consistent gain of 0.5 dB and more
is achieved when this technique is investigated with application of Maximum Transition
Run (MTR) codes. As the length of the PR target in PR equalisation increases, the gain
achieved using this novel technique consistently increases and reaches up to 1.2 dB in case
of EEPR4 target for a bit error rate of 10-5
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