255 research outputs found
Performance Enhancement of MIMO-OFDM using Redundant Residue Number System
Telecommunication industry requires high capacity networks with high data rates which are achieved through utilization of Multiple-Input-Multiple-Output (MIMO) communication along with Orthogonal Frequency Division Multiplexing (OFDM) system. Still, the communication channel suffers from noise, interference or distortion due to hardware design limitations, and channel environment, and to combat these challenges, and achieve enhanced performance; various error control techniques are implemented to enable the receiver to detect any possible received errors and correct it and thus; for a certain transmitted signal power the system would have lower Bit Error Rate (BER). The provided research focuses on Redundant Residue Number System (RRNS) coding as a Forward Error Correction (FEC) scheme that improves the performance of MIMO-OFDM based wireless communications in comparison with current methods as Low-Density Parity Check (LDPC) coders at the transmitter side or equalizers at receiver side. The Bit Error Rate (BER) performance over the system was measured using MATLAB tool for different simulated channel conditions, including the effect of signal amplitude reduction and multipath delay spreading. Simulation results had shown that RRNS coding scheme provides an enhancement in system performance over conventional error detection and correction coding schemes by utilizing the distinct features of Residue Number System (RNS)
Turbo Decoding and Detection for Wireless Applications
A historical perspective of turbo coding and turbo transceivers inspired by the generic turbo principles is provided, as it evolved from Shannon’s visionary predictions. More specifically, we commence by discussing the turbo principles, which have been shown to be capable of performing close to Shannon’s capacity limit. We continue by reviewing the classic maximum a posteriori probability decoder. These discussions are followed by studying the effect of a range of system parameters in a systematic fashion, in order to gauge their performance ramifications. In the second part of this treatise, we focus our attention on the family of iterative receivers designed for wireless communication systems, which were partly inspired by the invention of turbo codes. More specifically, the family of iteratively detected joint coding and modulation schemes, turbo equalization, concatenated spacetime and channel coding arrangements, as well as multi-user detection and three-stage multimedia systems are highlighted
Performance analysis and comparison of m x n zero forcing and MMSE equalizer based receiver for mimo wireless channel
Wireless transmission is affected by fading and interference effects which can be combated with equalizer.The useof MIMO system promises good improvement in terms of spectral efficency,link relaibility andSignal to Noise Ratio (SNR).The effect of fading and interference always causes an issue for signal recovery in wireless communication. Equalizationcompensates for Intersymbol Interference (ISI) created by multipath within time dispersive channels. This paper analyses theperformance of Zeroforcing and MMSE equalizer for MIMO wireless chaneels. The simulation results are obtained usingMatLab tool box version 7.0 at RF signal processing lab.The Bit Error Rate (BER) characteristics for the various transmittingand receiveing antennna is simulated in matlab tool box and many advantages and disdvantagesof the system is descrbed.The simulation results show that the equalizer based zero forcing receiver is good for noise free channel and is successfulin remving ISI,but MMSE is a better choice than ZF in terms of BER charateristics and under Noise performance
Asymptotic Performance of Linear Receivers in MIMO Fading Channels
Linear receivers are an attractive low-complexity alternative to optimal
processing for multi-antenna MIMO communications. In this paper we characterize
the information-theoretic performance of MIMO linear receivers in two different
asymptotic regimes. For fixed number of antennas, we investigate the limit of
error probability in the high-SNR regime in terms of the Diversity-Multiplexing
Tradeoff (DMT). Following this, we characterize the error probability for fixed
SNR in the regime of large (but finite) number of antennas.
As far as the DMT is concerned, we report a negative result: we show that
both linear Zero-Forcing (ZF) and linear Minimum Mean-Square Error (MMSE)
receivers achieve the same DMT, which is largely suboptimal even in the case
where outer coding and decoding is performed across the antennas. We also
provide an approximate quantitative analysis of the markedly different behavior
of the MMSE and ZF receivers at finite rate and non-asymptotic SNR, and show
that while the ZF receiver achieves poor diversity at any finite rate, the MMSE
receiver error curve slope flattens out progressively, as the coding rate
increases.
When SNR is fixed and the number of antennas becomes large, we show that the
mutual information at the output of a MMSE or ZF linear receiver has
fluctuations that converge in distribution to a Gaussian random variable, whose
mean and variance can be characterized in closed form. This analysis extends to
the linear receiver case a well-known result previously obtained for the
optimal receiver. Simulations reveal that the asymptotic analysis captures
accurately the outage behavior of systems even with a moderate number of
antennas.Comment: 48 pages, Submitted to IEEE Transactions on Information Theor
Wireless receiver designs: from information theory to VLSI implementation
Receiver design, especially equalizer design, in communications is a major concern in both academia and industry. It is a problem with both theoretical challenges and severe implementation hurdles. While much research has been focused on reducing complexity for optimal or near-optimal schemes, it is still common practice in industry to use simple techniques (such as linear equalization) that are generally significantly inferior. Although digital signal processing (DSP) technologies have been applied to wireless communications to enhance the throughput, the users' demands for more data and higher rate have revealed new
challenges. For example, to collect the diversity and combat fading channels, in addition to the transmitter designs that enable the diversity, we also require the receiver to be able to collect the prepared diversity.
Most wireless transmissions can be modeled as a linear block transmission system. Given a linear block transmission model assumption, maximum likelihood equalizers (MLEs) or near-ML decoders have been adopted at the receiver to collect diversity which is an important metric for performance, but these decoders exhibit high complexity. To reduce the decoding complexity, low-complexity equalizers, such as linear equalizers (LEs) and
decision feedback equalizers (DFEs) are often adopted. These methods, however, may not utilize the diversity enabled by the transmitter and as a result have degraded performance compared to
MLEs.
In this dissertation, we will present efficient receiver designs that achieve low bit-error-rate (BER), high mutual information, and low decoding complexity. Our approach is
to first investigate the error performance and mutual information of existing low-complexity equalizers to reveal the fundamental condition to achieve full diversity with LEs. We show that the fundamental condition for LEs to collect the same (outage) diversity as MLE is that the channels need to be constrained within a certain distance from orthogonality. The orthogonality deficiency (od) is adopted to quantify the distance of channels to orthogonality while other existing metrics are also introduced and compared. To meet the fundamental condition and achieve full diversity, a hybrid equalizer framework is proposed. The performance-complexity trade-off of hybrid equalizers is quantified by deriving the distribution of od.
Another approach is to apply lattice reduction (LR) techniques to improve the ``quality' of channel matrices. We present two widely adopted LR methods in wireless communications, the Lenstra-Lenstra-Lovasz (LLL) algorithm [51] and Seysen's algorithm (SA), by providing detailed descriptions and pseudo codes. The properties of output matrices of the LLL algorithm and SA are also quantified. Furthermore, other LR algorithms are also briefly introduced.
After introducing LR algorithms, we show how to adopt them into the wireless communication decoding process by presenting LR-aided hard-output detectors and LR-aided soft-output detectors for coded systems, respectively. We also analyze the performance of proposed efficient receivers from the perspective of diversity, mutual information, and complexity. We prove that LR techniques help to restore the diversity of low-complexity equalizers without increasing the complexity significantly.
When it comes to practical systems and simulation tool, e.g., MATLAB, only finite bits are adopted to represent numbers. Therefore, we revisit the diversity analysis for finite-bit represented systems. We illustrate that the diversity of MLE for systems with finite-bit representation is determined by the number of non-vanishing eigenvalues. It is also shown that although theoretically LR-aided detectors collect the same diversity as MLE in the real/complex field, it may show different diversity orders when finite-bit representation exists. Finally, the VLSI implementation of the complex LLL algorithms is provided to verify the practicality of our proposed designs.Ph.D.Committee Chair: Ma, Xiaoli; Committee Member: Anderson, David; Committee Member: Barry, John; Committee Member: Chen, Xu-Yan; Committee Member: Kornegay, Kevi
Performance Evaluation of Low Complexity Massive MIMO Techniques for SC-FDE Schemes
Massive-MIMO technology has emerged as a means to achieve 5G's ambitious goals;
mainly to obtain higher capacities and excellent performances without requiring the use of more
spectrum. In this thesis, focused on the uplink direction, we make a study of performance of low
complexity equalization techniques as well as we also approach the impact of the non-linear elements
located on the receivers of a system of this type. For that purpose, we consider a multi-user
uplink scenario through the Single Carrier with Frequency Domain Equalization (SC-FDE)
scheme. This seems to be the most appropriate due to the low energy consumption that it implies,
as well as being less favorable to the detrimental effects of high envelope fluctuations, that is, by
have a low Peak to Average Power Ratio (PAPR) comparing to other similar modulations, such
as the Orthogonal Frequency Division Multiplexing (OFDM). Due to the greater number of antennas
and consequent implementation complexity, the equalization processes for Massive-
MIMO schemes are aspects that should be simplified, that is, they should avoid the inversion of
matrices, contrary to common 4G, with the Zero Forcing (ZF) and Minimum Mean Square Error
(MMSE) techniques. To this end, we use low-complexity techniques, such as the Equal Gain
Combining (EGC) and the Maximum Ratio Combining (MRC). Since these algorithms are not
sufficiently capable of removing the entire Inter-Symbol Interference (ISI) and Inter-User Interference
(IUI), we combine them with iterative techniques, namely with the Iterative Block with
Decision Feedback Equalizer (IB-DFE) to completely remove the residual ISI and IUI. We also
take into account the hardware used in the receivers, since the effects of non-linear distortion can
impact negatively the performance of the system. It is expected a strong performance degradation
associated to the high quantization noise levels when implementing low-resolution Analog to
Digital Converters (ADCs). However, despite these elements with these configurations become
harmful to the performance of the majority of the systems, they are considered a desirable solution
for Massive-MIMO scenarios, because they make their implementation cheaper and more energy
efficient. In this way, we made a study of the impact in the performance by the low-resolution
ADCs. In this thesis we suggest that it is possible to bypass these negative effects by implementing
a number of receiving antennas far superior to the number of transmitting antennas
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