Norbert Goertz

Amplify-and-forward with partial relay selection

This letter offers a statistical analysis of the basic two-hop Amplify-and-Forward link, where the relay node is selected based on instantaneous and partial knowledge of the channel. In contrast with previously reported work, where relay selection requires global knowledge (2 hops) of the relaying link, the problem considered is interesting in practical ad-hoc systems, where only neighboring (1 hop) channel information is available to the nodes. The probability density function of the received signal-to-noise ratio for the considered relaying link is approximated in closed form, and an asymptotic exponential expression is proposed to simplify performance estimation.

Max-min relay selection for legacy amplify-and-forward systems with interference

In this paper, an amplify-and-forward (AF) cooperative strategy for interference limited networks is considered. In contrast to previously reported work, where the effect of interference is ignored, the effect of multi-user interference in AF schemes is analyzed. It is shown that the interference changes the statistical description of the conventional AF protocol and a statistical expression is subsequently derived. Asymptotic analysis of the expression shows that interference limits the diversity gain of the system and the related channel capacity is bounded by a stationary point. In addition, it is proven that previously proposed relay selection criteria for multi-relay scenarios become inefficient in the presence of interference. Based on consideration of the interference term, two extensions to the conventional max-min selection scheme suitable for different system setups are proposed. The extensions investigated are appropriate for legacy architectures with limitations on their flexibility where the max-min operation is pre-designed. A theoretical framework for selecting when to apply the proposed selection criteria is also presented. The algorithm investigated is based on some welldefined capacity approximations and incorporates the outage probabilities averaged over the fading statistics. Analytical results and simulation studies reveal enhancements of the proposed algorithm.

Optimization Issues for Cooperative Amplify-and-Forward Systems Over Block-Fading Channels

In this paper, we deal with an amplify-and-forward (AF) cooperative strategy in slot-based, block-fading environments. In contrast with previous schemes, which assume a constant channel during the cooperative frame (several slots), here, we relax this constraint and assume a classical quasi-static block- fading channel (constant for one slot). This additional degree of freedom modifies the behavior of the conventional nonorthogonal AF (NAF) schemes and generates a new block-fading NAF (BFNAF) protocol, where the source can usefully retransmit the same data during the cooperative slot. This new protocol is interesting at low spectral efficiencies, where diversity against fading is more important. To overcome performance degradation, which characterizes cooperative schemes at low signal-to-noise ratios (SNRs), an adaptive version of the considered schemes is also proposed, where cooperation is activated according to the outage behavior of the direct link. Moreover, an optimal hybrid protocol that allows intelligent switching between noncooperation, NAF, and BFNAF protocols is also proposed. Another issue that is discussed throughout this paper is the optimal power allocation of the investigated schemes. The proposed power-allocation strategy uses as an optimization criterion the well-defined asymptotic expressions of the outage probabilities, which are averaged over the fading statistics. The minimization (and avoidance for the nonhybrid protocols) of the required data feedback makes it suitable for practical ad hoc networks with crucial power constraints. The enhancement of the proposed schemes and the efficiency of the power allocation policy are shown by theoretical analysis and simulation results.

Robust Rate-Compatible Punctured LDPC Convolutional Codes

A family of robust rate-compatible (RC) punctured low-density parity-check convolutional codes (LDPC-CCs) is derived from a time-invariant LDPC-CC mother code by periodically puncturing encoded bits (variable nodes) with respect to several criteria: (1) ensuring the recoverability of punctured variable nodes, (2) minimizing the number of completely punctured cycle trapping sets (CPCTSs), and (3) minimizing the number of punctured variable nodes involved in short cycles. The influence of (1) and (3) on iterative decoding performance is felt most strongly in the waterfall region of the bit-error-rate (BER) curve, while (2) has a larger effect in the error floor, or high signal-to-noise ratio (SNR), region. We show that the length of the puncturing period is an important parameter when designing high rate punctured codes and, moreover, that extending the puncturing period can improve the decoding performance and extend the range of compatible rates. As examples, we obtain families of RC LDPC-CCs from several time-invariant LDPC-CC mother codes with monomial and binomial entries in their polynomial syndrome former matrices.

Graphical LASSO based Model Selection for Time Series

We propose a novel graphical model selection scheme for high-dimensional stationary time series or discrete time processes. The method is based on a natural generalization of the graphical LASSO algorithm, introduced originally for the case of i.i.d. samples, and estimates the conditional independence graph of a time series from a finite length observation. The graphical LASSO for time series is defined as the solution of an l1-regularized maximum (approximate) likelihood problem. We solve this optimization problem using the alternating direction method of multipliers. Our approach is nonparametric as we do not assume a finite dimensional parametric model, but only require the process to be sufficiently smooth in the spectral domain. For Gaussian processes, we characterize the performance of our method theoretically by deriving an upper bound on the probability that our algorithm fails. Numerical experiments demonstrate the ability of our method to recover the correct conditional independence graph from a limited amount of samples.

Nonlinear Long-Term Prediction of Speech Based on Truncated Volterra Series

Previous studies of nonlinear prediction of speech have been mostly focused on short-term prediction. This paper presents long-term nonlinear prediction based on second-order Volterra filters. It will be shown that the presented predictor can outperform conventional linear prediction techniques in terms of prediction gain and “whiter” residuals.

Joint channel estimation and activity detection for multiuser communication systems

We consider overloaded (non-orthogonal) code division multiple access multiuser wireless communication systems with many transmitting users and one central aggregation node, a typical scenario in e.g. machine-to-machine communications. The task of the central node is to detect the set of active devices and separate their data streams, whose number at any time instance is relatively small compared to the total number of devices in the system. We introduce a novel two-step detection procedure: the first step involves the simultaneous transmission of a pilot sequence used for identification of the active devices and the estimation of their respective channel coefficients. In the second step the payload is transmitted by all active devices and received synchronously at the central node. The first step reduces to a compressed sensing (CS) problem due to the relatively small number of simultaneously active devices. Using an efficient CS recovery scheme (approximate message passing), joint activity detection and channel estimation with high reliability is possible, even for extremely large-scale systems. This, in turn, reduces the data detection task to a simple overdetermined system of linear equations that is then solved by classical methods in the second step.

Free distance bounds for protograph-based regular LDPC convolutional codes

In this paper, asymptotic methods are used to form lower bounds on the free distance to constraint length ratio of several ensembles of regular, asymptotically good, protograph-based LDPC convolutional codes. In particular, we show that the free distance to constraint length ratio of the regular LDPC convolutional codes exceeds that of the minimum distance to block length ratio of the corresponding LDPC block codes.

Channel-Aware Scheduling with Resource-Sharing Constraints in Wireless Networks

In this paper, we consider the design of channel-aware scheduling policies for centralized wireless networks with resource-sharing constraints. The work is motivated by the objective to utilize the wireless system resources efficiently in addition to meeting the resource-sharing constraints. Our solutions are based on scheduling policies achieving close-to-capacity performance. We suggest two algorithms - an offline and an online solution - to properly adjust the weighting factors of the scheduling policy in order to achieve the required resource-sharing constraints.

A shared-relay cooperative diversity scheme based on joint channel and network coding in the multiple access channel

In this paper we propose a cooperative diversity scheme for the scenario of two sources sharing a single relay. The scheme uses algebraic code superposition relaying in the multiple access fading channel to create spatial diversity under the constraint of limited communications resources. We also describe in detail a novel computationally efficient message passing algorithm at the destinationpsilas decoder which extracts the substantial spatial diversity contained in the code superposition and signal superposition. The decoder is based on a sliding window structure where certain a posteriori LLRs are retained as a priori LLRs for the next decoding. We show that despite the simplicity of the proposed scheme, diversity gains are efficiently leveraged by the simple combination of channel coding at the sources and network coding at the relay.