arXiv subjects

Luca Barletta

Publications and source records attributed to Luca Barletta.

48 records · Page 3Linked to original sources

arXiv2018

On MIMO Channel Capacity with Output Quantization Constraints

The capacity of a Multiple-Input Multiple-Output (MIMO) channel in which the antenna outputs are processed by an analog linear combining network and quantized by a set of threshold quantizers is studied. The linear combining weights and quantization thresholds are selected from a set of possible configurations as a function of the channel matrix. The possible configurations of the combining network model specific analog receiver architectures, such as single antenna selection, sign quantization of the antenna outputs or linear processing of the outputs. An interesting connection between the capacity of this channel and a constrained sphere packing problem in which unit spheres are packed in a hyperplane arrangement is shown. From a high-level perspective, this follows from the fact that each threshold quantizer can be viewed as a hyperplane partitioning the transmitter signal space. Accordingly, the output of the set of quantizers corresponds to the possible regions induced by the hyperplane arrangement corresponding to the channel realization and receiver configuration. This connection provides a number of important insights into the design of quantization architectures for MIMO receivers; for instance, it shows that for a given number of quantizers, choosing configurations which induce a larger number of partitions can lead to higher rates.

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arXiv2017

A General Framework for Low-Resolution Receivers for MIMO Channels

The capacity of a discrete-time multi-input multi-output (MIMO) Gaussian channel with output quantization is investigated for different receiver architectures. A general formulation of this problem is proposed in which the antenna outputs are processed by analog combiners while sign quantizers are used for analog-to-digital conversion. To exemplify this approach, four analog receiver architectures of varying generality and complexity are considered: (a) multiple antenna selection and sign quantization of the antenna outputs, (b) single antenna selection and multilevel quantization, (c) multiple antenna selection and multilevel quantization, and (d) linear combining of the antenna outputs and multilevel quantization. Achievable rates are studied as a function of the number of available sign quantizers and compared among different architectures. In particular, it is shown that architecture (a) is sufficient to attain the optimal high signal-to-noise ratio performance for a MIMO receiver in which the number of antennas is larger than the number of sign quantizers. Numerical evaluations of the average performance are presented for the case in which the channel gains are i.i.d. Gaussian.

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arXiv2017

Capacity Outer Bound and Degrees of Freedom of Wiener Phase Noise Channels with Oversampling

The discrete-time Wiener phase noise channel with an integrate-and-dump multi-sample receiver is studied. A novel outer bound on the capacity with an average input power constraint is derived as a function of the oversampling factor. This outer bound yields the degrees of freedom for the scenario in which the oversampling factor grows with the transmit power $P$ as $P^α$. The result shows, perhaps surprisingly, that the largest pre-log that can be attained with phase modulation at high signal-to-noise ratio is at most $1/4$.

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arXiv2017

Stability and Instability Conditions for Slotted Aloha with Exponential Backoff

This paper provides stability and instability conditions for slotted Aloha under the exponential backoff (EB) model with geometric law $i\mapsto b^{-i-i_0}$, when transmission buffers are in saturation, i.e., always full. In particular, we prove that for any number of users and for $b>1$ the system is: (i) ergodic for $i_0 >1$, (ii) null recurrent for $0<i_0\le 1$, and (iii) transient for $i_0=0$. Furthermore, when referring to a system with queues and Poisson arrivals, the system is shown to be stable whenever EB in saturation is stable with throughput $λ_0$ and the system input rate is upper-bounded as $λ<λ_0$.

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arXiv2017

Capacity of Discrete-Time Wiener Phase Noise Channels to Within a Constant Gap

The capacity of the discrete-time channel affected by both additive Gaussian noise and Wiener phase noise is studied. Novel inner and outer bounds are presented, which differ of at most $6.65$ bits per channel use for all channel parameters. The capacity of this model can be subdivided in three regimes: (i) for large values of the frequency noise variance, the channel behaves similarly to a channel with circularly uniform iid phase noise; (ii) when the frequency noise variance is small, the effects of the additive noise dominate over those of the phase noise, while (iii) for intermediate values of the frequency noise variance, the transmission rate over the phase modulation channel has to be reduced due to the presence of phase noise.

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arXiv2016

Finite-length scaling based on belief propagation for spatially coupled LDPC codes

The equivalence of peeling decoding (PD) and Belief Propagation (BP) for low-density parity-check (LDPC) codes over the binary erasure channel is analyzed. Modifying the scheduling for PD, it is shown that exactly the same variable nodes (VNs) are resolved in every iteration than with BP. The decrease of erased VNs during the decoding process is analyzed instead of resolvable equations. This quantity can also be derived with density evolution, resulting in a drastic decrease in complexity. Finally, a scaling law using this quantity is established for spatially coupled LDPC codes.

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arXiv2015

Lower Bound on the Capacity of Continuous-Time Wiener Phase Noise Channels

A continuous-time Wiener phase noise channel with an integrate-and-dump multi-sample receiver is studied. A lower bound to the capacity with an average input power constraint is derived, and a high signal-to-noise ratio (SNR) analysis is performed. The capacity pre-log depends on the oversampling factor, and amplitude and phase modulation do not equally contribute to capacity at high SNR.

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arXiv2015

Upper Bound on the Capacity of Discrete-Time Wiener Phase Noise Channels

A discrete-time Wiener phase noise channel with an integrate-and-dump multi-sample receiver is studied. An upper bound to the capacity with an average input power constraint is derived, and a high signal-to-noise ratio (SNR) analysis is performed. If the oversampling factor grows as $\text{SNR}^α$ for $0\le α\le 1$, then the capacity pre-log is at most $(1+α)/2$ at high SNR.

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arXiv2014

On Continuous-Time White Phase Noise Channels

A continuous-time model for the additive white Gaussian noise (AWGN) channel in the presence of white (memoryless) phase noise is proposed and discussed. It is shown that for linear modulation the output of the baud-sampled filter matched to the shaping waveform represents a sufficient statistic. The analysis shows that the phase noise channel has the same information rate as an AWGN channel but with a penalty on the average signal-to-noise ratio, the amount of penalty depending on the phase noise statistic.

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arXiv2013

Tight Upper and Lower Bounds to the Information Rate of the Phase Noise Channel

Numerical upper and lower bounds to the information rate transferred through the additive white Gaussian noise channel affected by discrete-time multiplicative autoregressive moving-average (ARMA) phase noise are proposed in the paper. The state space of the ARMA model being multidimensional, the problem cannot be approached by the conventional trellis-based methods that assume a first-order model for phase noise and quantization of the phase space, because the number of state of the trellis would be enormous. The proposed lower and upper bounds are based on particle filtering and Kalman filtering. Simulation results show that the upper and lower bounds are so close to each other that we can claim of having numerically computed the actual information rate of the multiplicative ARMA phase noise channel, at least in the cases studied in the paper. Moreover, the lower bound, which is virtually capacity-achieving, is obtained by demodulation of the incoming signal based on a Kalman filter aided by past data. Thus we can claim of having found the virtually optimal demodulator for the multiplicative phase noise channel, at least for the cases considered in the paper.

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arXiv2013

An Asymptotically Efficient Backlog Estimate for Dynamic Frame Aloha

In this paper we investigate backlog estimation procedures for Dynamic Frame Aloha (DFA) in Radio Frequency Identification (RFID) environment. In particular, we address the tag identification efficiency with any tag number $N$, including $N\rightarrow\infty$. Although in the latter case efficiency $e^{-1}$ is possible, none of the solution proposed in the literature has been shown to reach such value. We analyze Schoute's backlog estimate, which is very attractive for its simplicity, and formally show that its asymptotic efficiency is 0.311. Leveraging the analysis, we propose the Asymptotic Efficient backlog Estimate (AE$^2$) an improvement of the Schoute's backlog estimate, whose efficiency reaches $e^{-1}$ asymptotically. We further show that AE$^2$ can be optimized in order to present an efficiency very close to $e^{-1}$ for practically any value of the population size. We also evaluate the loss of efficiency when the frame size is constrained to be a power of two, as required by RFID standards for DFA, and theoretically show that the asymptotic efficiency becomes 0.356.

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arXiv2013

A formal proof of the optimal frame setting for Dynamic-Frame Aloha with known population size

In Dynamic-Frame Aloha subsequent frame lengths must be optimally chosen to maximize throughput. When the initial population size ${\cal N}$ is known, numerical evaluations show that the maximum efficiency is achieved by setting the frame length equal to the backlog size at each subsequent frame; however, at best of our knowledge, a formal proof of this result is still missing, and is provided here. As byproduct, we also prove that the asymptotical efficiency in the optimal case is $e^{-1}$, provide upper and lower bounds for the length of the entire transmission period and show that its asymptotical behaviour is $\sim ne-ζ\ln (n)$, with $ζ=0.5/\ln(1-e^{-1})$.

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