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Lars K. Rasmussen

Publications and source records attributed to Lars K. Rasmussen.

34 records · Page 2Linked to original sources

Asymptotic Analysis of SU-MIMO Channels With Transmitter Noise and Mismatched Joint Decoding

Hardware impairments in radio-frequency components of a wireless system cause unavoidable distortions to transmission that are not captured by the conventional linear channel model. In this paper, a 'binoisy' single-user multiple-input multiple-output (SU-MIMO) relation is considered where the additional distortions are modeled via an additive noise term at the transmit side. Through this extended SU-MIMO channel model, the effects of transceiver hardware impairments on the achievable rate of multi-antenna point-to-point systems are studied. Channel input distributions encompassing practical discrete modulation schemes, such as, QAM and PSK, as well as Gaussian signaling are covered. In addition, the impact of mismatched detection and decoding when the receiver has insufficient information about the non-idealities is investigated. The numerical results show that for realistic system parameters, the effects of transmit-side noise and mismatched decoding become significant only at high modulation orders.

cs.IT↗

Rateless Codes for the Multi-Way Relay Channel

We consider distributed Luby transform (DLT) codes for efficient packet transmission in a multi-way relay network, where the links are modeled as erasure channels. Density evolution is applied for asymptotic performance analysis, and subsequently used in a linear-programming design framework for optimizing the degree distribution at the relay in terms of overhead. Moreover a buffer is introduced at the relay to enable efficient downlink transmission even if packets are lost during uplink transmission. Performance losses in terms of delay and/or erasure rates caused by link erasures during uplink transmission are thus alleviated. The proposed DLT codes provide significant improvements in overhead and decoded erasure rates. Numerical results for finite-length codes follow closely the asymptotic analysis. Our results demonstrate that the proposed buffer-based DLT codes outperform its counterparts for lossy uplink transmission.

cs.IT↗

Buffer-Based Distributed LT Codes

We focus on the design of distributed Luby transform (DLT) codes for erasure networks with multiple sources and multiple relays, communicating to a single destination. The erasure-floor performance of DLT codes improves with the maximum degree of the relay-degree distribution. However, for conventional DLT codes, the maximum degree is upper-bounded by the number of sources. An additional constraint is that the sources are required to have the same information block length. We introduce a $D$-bit buffer for each source-relay link, which allows the relay to select multiple encoded bits from the same source for the relay-encoding process; thus, the number of sources no longer limits the maximum degree at the relay. Furthermore, the introduction of buffers facilitates the use of different information block sizes across sources. Based on density evolution we develop an asymptotic analytical framework for optimization of the relay-degree distribution. We further integrate techniques for unequal erasure protection into the optimization framework. The proposed codes are considered for both lossless and lossy source-relay links. Numerical examples show that there is no loss in erasure performance for transmission over lossy source-relay links as compared to lossless links. Additional delays, however, may occur. The design framework and our contributions are demonstrated by a number of illustrative examples, showing the improvements obtained by the proposed buffer-based DLT codes.

cs.IT↗

Causal/Predictive Imperfect Channel State Information in Block-Fading Channels

We consider a multi-input multi-output (MIMO) block-fading channel with a general model for channel state information at the transmitter (CSIT). The model covers systems with causal CSIT, where only CSIT of past fading blocks is available, and predictive CSIT, where CSIT of some future fading blocks is available. The optimal diversity-multiplexing tradeoff (DMT) and rate-diversity tradeoff (RDT) of the channel are studied under long-term power constraints. The impact of imperfect (mismatched) CSIT on the optimal DMT and RDT is also investigated. Our results show the outage diversity gain obtained by providing imperfect causal/predictive CSIT, leading to new insights into system design and analysis.

cs.IT↗

SEK: Sparsity exploiting $k$-mer-based estimation of bacterial community composition

Motivation: Estimation of bacterial community composition from a high-throughput sequenced sample is an important task in metagenomics applications. Since the sample sequence data typically harbors reads of variable lengths and different levels of biological and technical noise, accurate statistical analysis of such data is challenging. Currently popular estimation methods are typically very time consuming in a desktop computing environment. Results: Using sparsity enforcing methods from the general sparse signal processing field (such as compressed sensing), we derive a solution to the community composition estimation problem by a simultaneous assignment of all sample reads to a pre-processed reference database. A general statistical model based on kernel density estimation techniques is introduced for the assignment task and the model solution is obtained using convex optimization tools. Further, we design a greedy algorithm solution for a fast solution. Our approach offers a reasonably fast community composition estimation method which is shown to be more robust to input data variation than a recently introduced related method. Availability: A platform-independent Matlab implementation of the method is freely available at http://www.ee.kth.se/ctsoftware; source code that does not require access to Matlab is currently being tested and will be made available later through the above website.

q-bio.GN↗

Large-System Analysis of Correlated MIMO Multiple Access Channels with Arbitrary Signaling in the Presence of Interference

Presence of multiple antennas on both sides of a communication channel promises significant improvements in system throughput and power efficiency. In effect, a new class of large multiple-input multiple-output (MIMO) communication systems has recently emerged and attracted both scientific and industrial attention. To analyze these systems in realistic scenarios, one has to include such aspects as co-channel interference, multiple access and spatial correlation. In this paper, we study the properties of correlated MIMO multiple-access channels in the presence of external interference. Using the replica method from statistical physics, we derive the ergodic sum-rate of the communication for arbitrary signal constellations when the numbers of antennas at both ends of the channel grow large. Based on these asymptotic expressions, we also address the problem of sum-rate maximization using statistical channel information and linear precoding. The numerical results demonstrate that when the interfering terminals use discrete constellations, the resulting interference becomes easier to handle compared to Gaussian signals. Thus, it may be possible to accommodate more interfering transmitter-receiver pairs within the same area as compared to the case of Gaussian signals. In addition, we demonstrate numerically for the Gaussian and QPSK signaling schemes that it is possible to design precoder matrices that significantly improve the achievable rates at low-to-mid range of signal-to-noise ratios when compared to isotropic precoding.

cs.IT↗

MIMO ARQ with Multi-bit Feedback: Outage Analysis

We study the asymptotic outage performance of incremental redundancy automatic repeat request (INR-ARQ) transmission over the multiple-input multiple-output (MIMO) block-fading channels with discrete input constellations. We first show that transmission with random codes using a discrete signal constellation across all transmit antennas achieves the optimal outage diversity given by the Singleton bound. We then analyze the optimal SNR-exponent and outage diversity of INR-ARQ transmission over the MIMO block-fading channel. We show that a significant gain in outage diversity is obtained by providing more than one bit feedback at each ARQ round. Thus, the outage performance of INR-ARQ transmission can be remarkably improved with minimal additional overhead. A suboptimal feedback and power adaptation rule, which achieves the optimal outage diversity, is proposed for MIMO INR-ARQ, demonstrating the benefits provided by multi-bit feedback.

cs.IT↗

Adaptive Decoding of LDPC Codes with Binary Messages

A novel adaptive binary decoding algorithm for LDPC codes is proposed, which reduces the decoding complexity while having a comparable or even better performance than corresponding non-adaptive alternatives. In each iteration the variable node decoders use the binary check node decoders multiple times; each single use is referred to as a sub-iteration. To process the sequences of binary messages in each iteration, the variable node decoders employ pre-computed look-up tables. These look-up tables as well as the number of sub-iterations per iteration are dynamically adapted during the decoding process based on the decoder state, represented by the mutual information between the current messages and the syndrome bits. The look-up tables and the number of sub-iterations per iteration are determined and optimized using density evolution. The performance and the complexity of the proposed adaptive decoding algorithm is exemplified by simulations.

cs.IT↗

Power Allocation for Fading Channels with Peak-to-Average Power Constraints

Power allocation with peak-to-average power ratio constraints is investigated for transmission over Nakagami-m fading channels with arbitrary input distributions. In the case of delay-limited block-fading channels, we find the solution to the minimum outage power allocation scheme with peak-to-average power constraints and arbitrary input distributions, and show that the signal-to-noise ratio exponent for any finite peak-to-average power ratio is the same as that of the peak-power limited problem, resulting in an error floor. In the case of the ergodic fully-interleaved channel, we find the power allocation rule that yields the maximal information rate for an arbitrary input distribution and show that capacities with peak-to-average power ratio constraints, even for small ratios, are very close to capacities without peak-power restrictions.

cs.IT↗

A Tight Lower Bound to the Outage Probability of Discrete-Input Block-Fading Channels

In this correspondence, we propose a tight lower bound to the outage probability of discrete-input Nakagami-m block-fading channels. The approach permits an efficient method for numerical evaluation of the bound, providing an additional tool for system design. The optimal rate-diversity trade-off for the Nakagami-m block-fading channel is also derived and a tight upper bound is obtained for the optimal coding gain constant.

cs.IT↗

Power Allocation for Discrete-Input Non-Ergodic Block-Fading Channels

We consider power allocation algorithms for fixed-rate transmission over Nakagami-m non-ergodic block-fading channels with perfect transmitter and receiver channel state information and discrete input signal constellations under both short- and long-term power constraints. Optimal power allocation schemes are shown to be direct applications of previous results in the literature. We show that the SNR exponent of the optimal short-term scheme is given by the Singleton bound. We also illustrate the significant gains available by employing long-term power constraints. Due to the nature of the expressions involved, the complexity of optimal schemes may be prohibitive for system implementation. We propose simple sub-optimal power allocation schemes whose outage probability performance is very close to the minimum outage probability obtained by optimal schemes.

cs.IT↗

Power Allocation for Discrete-Input Delay-Limited Fading Channels

We consider power allocation algorithms for fixed-rate transmission over Nakagami-m non-ergodic block-fading channels with perfect transmitter and receiver channel state information and discrete input signal constellations, under both short- and long-term power constraints. Optimal power allocation schemes are shown to be direct applications of previous results in the literature. We show that the SNR exponent of the optimal short-term scheme is given by m times the Singleton bound. We also illustrate the significant gains available by employing long-term power constraints. In particular, we analyze the optimal long-term solution, showing that zero outage can be achieved provided that the corresponding short-term SNR exponent with the same system parameters is strictly greater than one. Conversely, if the short-term SNR exponent is smaller than one, we show that zero outage cannot be achieved. In this case, we derive the corresponding long-term SNR exponent as a function of the Singleton bound. Due to the nature of the expressions involved, the complexity of optimal schemes may be prohibitive for system implementation. We therefore propose simple sub-optimal power allocation schemes whose outage probability performance is very close to the minimum outage probability obtained by optimal schemes. We also show the applicability of these techniques to practical systems employing orthogonal frequency division multiplexing.

cs.IT↗

Optimal Throughput-Diversity-Delay Tradeoff in MIMO ARQ Block-Fading Channels

In this paper, we consider an automatic-repeat-request (ARQ) retransmission protocol signaling over a block-fading multiple-input, multiple-output (MIMO) channel. Unlike previous work, we allow for multiple fading blocks within each transmission (ARQ round), and we constrain the transmitter to fixed rate codes constructed over complex signal constellations. In particular, we examine the general case of average input-power-constrained constellations as well as the practically important case of finite discrete constellations. This scenario is a suitable model for practical wireless communications systems employing orthogonal frequency division multiplexing techniques over a MIMO ARQ channel. Two cases of fading dynamics are considered, namely short-term static fading where channel fading gains change randomly for each ARQ round, and long-term static fading where channel fading gains remain constant over all ARQ rounds pertaining to a given message. As our main result, we prove that for the block-fading MIMO ARQ channel with discrete input signal constellation satisfying a short-term power constraint, the optimal signal-to-noise ratio (SNR) exponent is given by a modified Singleton bound, relating all the system parameters. To demonstrate the practical significance of the theoretical analysis, we present numerical results showing that practical Singleton-bound-achieving maximum distance separable codes achieve the optimal SNR exponent.

cs.IT↗

Design of Rate-Compatible Serially Concatenated Convolutional Codes

Recently a powerful class of rate-compatible serially concatenated convolutional codes (SCCCs) have been proposed based on minimizing analytical upper bounds on the error probability in the error floor region. Here this class of codes is further investigated by combining analytical upper bounds with extrinsic information transfer charts analysis. Following this approach, we construct a family of rate-compatible SCCCs with good performance in both the error floor and the waterfall regions over a broad range of code rates.

cs.IT↗

Non-Data-Aided Parameter Estimation in an Additive White Gaussian Noise Channel

Non-data-aided (NDA) parameter estimation is considered for binary-phase-shift-keying transmission in an additive white Gaussian noise channel. Cramer-Rao lower bounds (CRLBs) for signal amplitude, noise variance, channel reliability constant and bit-error rate are derived and it is shown how these parameters relate to the signal-to-noise ratio (SNR). An alternative derivation of the iterative maximum likelihood (ML) SNR estimator is presented together with a novel, low complexity NDA SNR estimator. The performance of the proposed estimator is compared to previously suggested estimators and the CRLB. The results show that the proposed estimator performs close to the iterative ML estimator at significantly lower computational complexity.

cs.IT↗

Nonlinear MMSE Multiuser Detection Based on Multivariate Gaussian Approximation

In this paper, a class of nonlinear MMSE multiuser detectors are derived based on a multivariate Gaussian approximation of the multiple access interference. This approach leads to expressions identical to those describing the probabilistic data association (PDA) detector, thus providing an alternative analytical justification for this structure. A simplification to the PDA detector based on approximating the covariance matrix of the multivariate Gaussian distribution is suggested, resulting in a soft interference cancellation scheme. Corresponding multiuser soft-input, soft-output detectors delivering extrinsic log-likelihood ratios are derived for application in iterative multiuser decoders. Finally, a large system performance analysis is conducted for the simplified PDA, showing that the bit error rate performance of this detector can be accurately predicted and related to the replica method analysis for the optimal detector. Methods from statistical neuro-dynamics are shown to provide a closely related alternative large system prediction. Numerical results demonstrate that for large systems, the bit error rate is accurately predicted by the analysis and found to be close to optimal performance.

cs.IT↗