Dissertation•
On Linear Transmission Systems
01 Jan 2012-
TL;DR: The object in Part I is to study the impact of both the signaling rate and the pulse shape on the information rate of single antenna, single carrier linear modulation systems, and a iterative optimization method is developed, which produces precoders improving upon the best known ones in the literature.
Abstract: This thesis is divided into two parts. Part I analyzes the information rate of single antenna, single carrier linear modulation systems. The information rate of a system is the maximum number of bits that can be transmitted during a channel usage, and is achieved by Gaussian symbols. It depends on the underlying pulse shape in a linear modulated signal and also the signaling rate, the rate at which the Gaussian symbols are transmitted. The object in Part I is to study the impact of both the signaling rate and the pulse shape on the information rate.
Part II of the thesis is devoted to multiple antenna systems (MIMO), and more specifically to linear precoders for MIMO channels. Linear precoding is a practical scheme for improving the performance of a MIMO system, and has been studied intensively during the last four decades. In practical applications, the symbols to be transmitted are taken from a discrete alphabet, such as quadrature amplitude modulation (QAM), and it is of interest to find the optimal linear precoder for a certain performance measure of the MIMO channel. The design problem depends on the particular performance measure and the receiver structure. The main difficulty in finding the optimal precoders is the discrete nature of the problem, and mostly suboptimal solutions are proposed. The problem has been well investigated when linear receivers are employed, for which optimal precoders were found for many different performance measures. However, in the case of the optimal maximum likelihood (ML) receiver, only suboptimal constructions have been possible so far. Part II starts by proposing new novel, low complexity, suboptimal precoders, which provide a low bit error rate (BER) at the receiver. Later, an iterative optimization method is developed, which produces precoders improving upon the best known ones in the literature. The resulting precoders turn out to exhibit a certain structure, which is then analyzed and proved to be optimal for large alphabets.
Citations
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Dissertation•
01 Jan 2013
TL;DR: A framework to design reduced-complexity receivers for FTN and general linear channels that achieve optimal or near-optimal performance and an improvement of the minimum phase conversion that sharpens the focus of the ISI model energy is proposed.
Abstract: Fast and reliable data transmission together with high bandwidth efficiency are important design aspects in a modern digital communication system. Many different approaches exist but in this thesis bandwidth efficiency is obtained by increasing the data transmission rate with the faster-than-Nyquist (FTN) framework while keeping a fixed power spectral density (PSD). In FTN consecutive information carrying symbols can overlap in time and in that way
introduce a controlled amount of intentional intersymbol interference (ISI). This technique was introduced already in 1975 by Mazo and has since then been extended in many directions.
Since the ISI stemming from practical FTN signaling can be of significant duration, optimum detection with traditional methods is often prohibitively complex, and alternative equalization methods with acceptable complexity-performance tradeoffs are needed. The key objective of this thesis is therefore to design reduced-complexity receivers for FTN and general linear channels that achieve optimal or near-optimal performance. Although the performance of a detector can be measured by several means, this thesis is restricted to bit error rate (BER) and mutual information results. FTN signaling is applied in two ways: As a separate uncoded narrowband communication system or in a coded scenario consisting of a convolutional encoder, interleaver and the inner ISI mechanism in serial concatenation. Turbo equalization where soft information in the form of log likelihood ratios (LLRs) is exchanged between the equalizer and the decoder is a commonly used decoding technique for coded FTN signals.
The first part of the thesis considers receivers and arising stability problems when working within the white noise constraint. New M-BCJR algorithms for turbo equalization are proposed and compared to reduced-trellis VA and BCJR benchmarks based on an offset label idea. By adding a third low-complexity M-BCJR recursion, LLR quality is improved for practical values of M. M here measures the reduced number of BCJR computations for each data symbol. An improvement of the minimum phase conversion that sharpens the focus of the ISI model energy is proposed. When combined with a delayed and slightly mismatched receiver, the decoding allows a smaller M without significant loss in BER.
The second part analyzes the effect of the internal metric calculations on the performance of Forney- and Ungerboeck-based reduced-complexity equalizers of the M-algorithm type for both ISI and multiple-input multiple-output (MIMO) channels. Even though the final output of a full-complexity equalizer is identical for both models, the internal metric calculations are in general different. Hence, suboptimum methods need not produce the same final output. Additionally, new models working in between the two extremes are proposed and evaluated. Note that the choice of observation model does not impact the detection complexity as the underlying algorithm is unaltered.
The last part of the thesis is devoted to a different complexity reducing approach. Optimal channel shortening detectors for linear channels are optimized from an information theoretical perspective. The achievable information rates of the shortened models as well as closed form expressions for all components of the optimal detector of the class are derived. The framework used in this thesis is more general than what has been previously used within the area.
2 citations
References
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16 Aug 2004
TL;DR: The expected capability of the SC-FDE is always poorer than that of OFDM in frequency-selective fading channel, and it is closer to of orthogonal frequency-division multiplexing in channel with lower delay spread.
Abstract: This paper deals with the capacity behavior of single carrier modulation with frequency-domain equalization (SC-FDE) systems in broad-band multipath fading environments for the case where the channel is unknown at the transmitter and perfectly known at the receiver. The capacity performance of SC-FDE system is compared with that of orthogonal frequency-division multiplexing (OFDM) system. And the influence of the propagation environment and system parameters on capacity of these systems is studied. A useful conclusion is obtained that the expected capability of the SC-FDE is always poorer than that of OFDM in frequency-selective fading channel, and it is closer to OFDM in channel with lower delay spread. Furthermore, it is found that although the expected capacity of SC-FDE decreases with increasing delay spread, the outage probability may decrease as a result of the frequency diversity.
72 citations
01 Jan 1988
69 citations
31 Oct 2005
TL;DR: The power allocation policy, referred to as mercury/waterfilling, that maximizes the sum mutual information over parallel channels with arbitrary input constellations is given.
Abstract: For parallel independent Gaussian-noise channels with an aggregate power constraint, independent Gaussian inputs whose powers are allocated according to the waterfilling policy maximize the sum mutual information. In practice, however, discrete signalling constellations such as m-PSK or m-QAM are used in lieu of the ideal Gaussian signals. This paper gives the power allocation policy, referred to as mercury/waterfilling, that maximizes the sum mutual information over parallel channels with arbitrary input constellations
51 citations
TL;DR: This paper derives expressions for the sum rate in terms of the average energy of the precoded vector, and uses this to derive a high signal-to-noise ratio (SNR) closed-form upper bound, which is shown to be tight via simulation.
Abstract: This paper considers the multiuser multiple-input multiple-output (MIMO) broadcast channel. We consider the case where the multiple transmit antennas are used to deliver independent data streams to multiple users via vector perturbation. We derive expressions for the sum rate in terms of the average energy of the precoded vector, and use this to derive a high signal-to-noise ratio (SNR) closed-form upper bound, which we show to be tight via simulation. We also propose a modification to vector perturbation where different rates can be allocated to different users. We conclude that for vector perturbation precoding most of the sum rate gains can be achieved by reducing the rate allocation problem to the user selection problem. We then propose a low-complexity user selection algorithm that attempts to maximize the high-SNR sum rate upper bound. Simulations show that the algorithm outperforms other user selection algorithms of similar complexity.
50 citations
TL;DR: In this letter, the asymptotic information rate of faster-than-Nyquist (FTN) signaling is examined when the data sequence consists of independent and identically distributed (i.i.d.d.) binary symbols and it is shown that, as the FTN rate tends to infinity, the information rate converges to that of theFTN signaling with Gaussian symbols.
Abstract: In this letter, the asymptotic information rate of faster-than-Nyquist (FTN) signaling is examined when the data sequence consists of independent and identically distributed (i.i.d.) binary symbols. It is shown that, as the FTN rate tends to infinity, the information rate converges to that of the FTN signaling with i.i.d. Gaussian symbols. This leads to the optimality of the i.i.d. binary FTN signaling in the sense that the channel capacity can be asymptotically achieved by employing a transmit pulse that results in the same power spectral density as the water-filling solution.
48 citations