In vehicular communications, accurate modeling of real-world radio propagation channels is essential. To this end, we propose a novel stochastic model, namedVehicular-Tapped Delay-Line(V-TDL) that accurately captures the statistical behavior of multipath channels characterized by path-dependent gains, delays, and Doppler shifts. V-TDL supports diverse traffic conditions and road geometries by generating channel instances through well-established probability distributions. Also, it effectively models the parameters of the distributions through realistic geometry-based simulations, achieving the accuracy of a ray-tracing-based model while maintaining the low complexity of a purely stochastic approach. In contrast to existing models, V-TDL accounts for the correlation between propagation paths. Our findings show that this correlation is inherent in high-speed vehicular environments and neglecting it leads to a significant overestimation of channel diversity and system performance. We compare our model to existing alternatives to assess the performance of OTFS and OFDM modulations. The results demonstrate that, unlike traditional models such as the 3GPP EVA, V-TDL captures variations in channel diversity influenced by traffic intensity and road geometry, which impact the OTFS and OFDM performance. Although OTFS is penalized by path correlation, it consistently outperforms OFDM in all evaluated vehicular environments, confirming its suitability for high-speed vehicular communication scenarios.

In this paper, we consider an orthogonal time frequency space (OTFS) system in time-varying channels with overspread Doppler shifts, typically found in non-terrestrial multi-satellite links. The overspread Doppler shifts with magnitude greater than half of the subcarrier spacing, result in aliased Doppler shifts in the delay-Doppler (DD) domain due to the OTFS modulo operation. This makes channel estimation very challenging and the traditional channel estimation methods become ineffective. To address this challenge, we propose a DD training frame and a two-stage channel estimation method. The training frame comprises a cosine pilot signal and a pilot symbol. In the first stage of the channel estimation, the pilot symbol in the DD domain is utilized to estimate the delays, aliased Doppler shifts, and channel gains of the propagation paths. In the second stage, the received time domain signal is converted into the frequency domain to detect the peaks of all the Doppler shifts using the cosine pilot signal. Then, we present a threshold-based method to pair the estimated actual Doppler shifts with their corresponding delays and channel gains. The complexity of the proposed channel estimation is also discussed. Finally, the performance of the proposed channel estimation is validated in terms of the normalized mean square error (NMSE) and bit error rate (BER) in various scenarios.

This paper studies the coherent capacity of noiselimited satellite communications between a serving satellite from a mega-constellation and a ground user. The satellite megaconstellation is stochastically modelled as a non-homogeneous binomial point process at the time instance when inter-satellite handover occurs, and thereafter the chosen satellite is on a deterministic orbit that persistently serves the ground user until it is no longer visible. The persistent satellite capacity is derived as an integral closed-form for a handover strategy that randomly chooses a visible satellite. Additional handover strategies are studied by estimating their persistent capacities using Monte Carlo simulations. The nearest-satellite handover strategy outperforms the random handover strategy but is improved upon with a handover strategy that chooses the satellite with the maximum capacity over its projected orbit. The gap between the persistent capacity and the non-persistent capacity from the literature is significant, motivating the use of persistent capacity for accurate analysis of satellite mega-constellations.

Codes with locality without any global paritycheck constraints apart from those generated by local codes' constraints have recently found a unique application in decentralized systems. In response to this, we proposed in previous work, a new class of block circulant (BC) codes possessing certain structure in the arrangement of parity-check constraints referred to as a block circulant topology. The BC topology$T_{[\mu, \lambda, \omega]}(\rho)$and$\mathbf{B C}$codes$C_{\mathbf{B C}}[\mu, \lambda, \omega, \rho]$are parameterized by integers$\lambda \geq 2, \omega \geq 2, \rho \geq 2$and$\mu$a multiple of$\lambda$. In this work, we show that the rate and the minimum distance of the BC code scale with corresponding metrics of its local codes in a manner that can not be realized by well-known linear array and product topologies, thus widening the possible regime of operation. We also provide an efficient erasure-correcting decoder for$C_{\mathbf{B C}}[\mu, \lambda=3, \omega, \rho]$, while such a decoder was earlier known only for$\lambda=2$. The decoding algorithm uses a novel mechanism that iteratively corrects erasures from either a single or a triplet of local codes. We show that the minimum distance of$C_{\mathbf{B C}}[\mu, \lambda=3, \omega, \rho]$is$3 \rho+1$, whereas the same result was earlier available under a constraint that$\mu=2^{a} \cdot 3$for some integer$a$.

In nanopore sequencers, the realtime conductance of the nanopore is influenced by the blockage level at its narrowest region, which changes as nucleobases along an analyte DNA molecule enter one after another. This sequence of conductance levels (the signature) is an important DNA sequence-specific property that can be used to infer the DNA sequence from the nanopore signal output (a read). These signatures are challenging to estimate because DNA translocates at a variable speed and noise can obscure small changes in the nanopore conductance. In this paper, we consider the nanopore channel in the setting where the dwell times of each nucleobase follows a geometric distribution, and the signature is estimated from the pointwise average of many reads of the same DNA sequence. We show that the singular value decomposition of the averaged channel matrix can be written in terms of discrete Legendre polynomials, giving us a spectral decomposition of nanopore signatures. This decomposition also enables a fast method to estimate the DNA signature from a large number of noisy reads.

A Batch Private Information Retrieval (batch-PIR) scheme allows a client to retrieve multiple data items from a database without revealing them to the storage server(s). Most existing approaches for batch - Pirare based on batch codes, in particular, probabilistic batch codes (PBC) (Angel et al. S&P'18), which incur large storage overheads. In this work, we show that zero storage overhead is achievable for tree-shaped databases. In particular, we develop TreePIR, a novel approach tailored made for private retrieval of the set of nodes along an arbitrary root-to-leaf path in a Merkle tree with no storage redundancy. This type of tree has been widely implemented in many real-world systems such as Amazon DynamoDB, Google's Certificate Transparency, and blockchains. Tree nodes along a root-to-leaf path forms the well-known Merkle proof. TreePIR, which employs a novel tree coloring, outperforms PBC, a fundamental component in state-of-the-art batch-PIR schemes (Angel et al. S&P'18, Mughees-Ren S&P'23, Liu et al. S&P'24), in all metrics, achieving 3 ×lower total storage and 1.5-3 ×lower computation and communication costs. Most notably, TreePIR has 8-160× lower setup time and its polylog-complexity indexing algorithm is 19–160 ×faster than PBC for trees of 210_224leaves.

The growing interest in Orthogonal Time Frequency Space (OTFS) modulation for vehicular communication systems requires the validation of its advantages using suitable channel models capable of emulating the dynamic and geometric complexities of vehicle-to-infrastructure systems. This paper presents a novel, realistic geometric-based channel model, called V-CORE, specifically designed for evaluating the performance of OTFS in vehicular scenarios. Our model accurately characterizes the scattered paths by exploiting the radar cross-section of the vehicles that populate a road according to a given vehicular traffic intensity. Multiple road scenarios with different geometry and vehicle velocities are considered, resulting in a flexible tool to evaluate system performance in different traffic contexts. The V-CORE model provides the channel variables, particularly relevant to OTFS implementation, such as multipath Doppler shift and delay. We assess the performance of OTFS against that of OFDM under different road structures, traffic intensity, and vehicle velocities. Further, we compare the proposed V-CORE model to the Extended Vehicular A model and demonstrate that ours provides a deeper insight into performance in high-speed vehicular scenarios.

We explored the ubiquitous phenomenon of serial scammers, each of whom deployed dozens to thousands of addresses to conduct a series of similar Rug Pulls on popular decentralized exchanges.We first constructed two datasets of around 384,000 scammer addresses behind all one-day Simple Rug Pulls on Uniswap (Ethereum) and Pancakeswap (BSC), and identified distinctive scam patterns including star, chain, and major (scam-funding) flow.These patterns, which collectively cover about 40% of all scammer addresses in our datasets, reveal typical ways scammers run multiple Rug Pulls and organize the money flow among different addresses.We then studied the more general concept of scam cluster, which comprises scammer addresses linked together via direct ETH/BNB transfers or behind the same scam pools.We found that scam token contracts are highly similar within each cluster (average similarities > 70%) and dissimilar across different clusters (average similarities < 30%), corroborating our view that each cluster belongs to the same scammer/scam organization.Lastly, we analyze the scam profit of individual scam pools and clusters, employing a novel cluster-aware profit formula that takes into account the important role of wash traders.The analysis shows that the existing formula inflates the profit by at least 32% on Uniswap and 24% on Pancakeswap.

A general satellite channel model is proposed for communications between a rapidly moving low Earth orbit (LEO) satellite in a mega-constellation and a stationary user on Earth. The channel uses a non-homogeneous binomial point process (NBPP) for modelling the satellite positions, marked with an ascending/descending binary random variable for modelling the satellite directions. Using the marked NBPP, we derive the probability distributions of power gain, propagation delay, and Doppler shift, resulting in a stochastic signal propagation model for the mega-constellation geometry in isolation of other effects. This forms the basis for our proposed channel model as a randomly time-varying channel. The scattering function of this channel is derived to characterise how the received power is spread in the delay-Doppler domain. Global channel parameters such as path loss and channel spread are analysed in terms of the scattering function. The channel statistics and the global channel parameters closely match realistic orbit simulations of the Starlink constellation.

In this paper, we design a family of [n, k, d] block circulant codes that consist of many [n0≪n, k0≪k, d0d] local codes and that satisfy two properties: (1) the code supports distributed decoding of up to (d− 1) erasures relying only on local codes without a central coordinator, and (2) it is amenable to low complexity verification of code symbols using a cryptographic commitment scheme. These properties make the code ideal for use in protocols that address the data availability problem in blockchain networks. Moreover, the code outperforms the currently used 2D Reed-Solomon (RS) code with a larger relative minimum distance (d/n), as desired in the protocol, for a given rate (k/n) in the high-rate regime. The code is designed in two steps. First, we develop the topology, i.e., the structure of linear dependence relations among code symbols, and define it as the block circulant topologyT[μ,λ,ω](ρ). In this topology, there are μ local codes, each constrained by ρ parity checks. The set of symbols of a local code intersects with another in a uniform pattern, determined by two parameters, namely theoverlap factorλ and theoverlap widthω. Next, we instantiate the topology, i.e., specify the coefficients of the linear dependence relations, to construct the block circulant codesCBC[μ, λ, ω, ρ]. Every local code is a [λω+ρ, λω, ρ+1] generalized RS code. The block circulant code hasn= μ(ρ + ω), k = μω and we show that, under certain conditions,d= λρ + 1. For λ = 2, we prove that d = 2ρ+1 always, and provide an efficient, parallelizable erasure-correcting decoder that fully recovers the codeword when there are ≤ 2ρ erasures. The decoder uses a novel decoding mechanism that iteratively recovers erasures from either local codes or pairs of them.

Channels with noisy duplications have recently been used to model the nanopore sequencer. This paper extends some foundational information-theoretic results to this new scenario. We prove the asymptotic equipartition property (AEP) for noisy duplication processes based on ergodic Markov processes. A consequence is that the noisy duplication channel is information stable for ergodic Markov sources, and therefore the channel capacity constrained to Markov sources is the Markov -constrained Shannon capacity. We use the AEP to estimate lower bounds on the capacity of the binary symmetric channel with Bernoulli and geometric duplications using Monte Carlo simulations. In addition, we relate the AEP for noisy duplication processes to the AEP for hidden semi-Markov processes.

A family of$(n=2^{\ell}.M=2^{k_{\ell}}\ . \ d=2)$, binary constant-weight codes for any positive integer$\ell > 3, k_{\ell}= \displaystyle \frac{\ell(\ell+1)}{9}-1$was recently proposed in literature [1]. As infor-mation is encoded in the gaps (cyclically counted) between successive 1 's, we refer to these codes as cyclic-gap constant weight codes denoted by$C_{G}[\ell$. These codes admit very low-complexity algorithms for mapping and demapping between message and codeword vectors, fully eliminating the need for costly computations of binomial coefficients. In this paper, we study maximum-likelihood (ML) decoding of these codes under additive white Gaussian noise channels. Since the minimum distance of the code$d=2$, hard-decision decoders can not correct errors. Motivated by the error-correcting capability of soft-decision Wagner-rule decoder for single-parity-check codes, we derive an ML decoder for$C_{G}[\ell$. We also derive a low-complexity approximation of the ML decoder with a time-complexity of$O(n\log n^{\backslash },$. The algorithm is based on a novel technique of traversal through the Hasse diagram of a partially ordered set of all ℓ-subsets of$\{1, 2, \ldots, n\}$in a breadth-first manner. Our approach is applicable to decoding of any binary constant-weight code and therefore is of general interest. We simulate the performance of the low-complexity decoder for the$(8, 32, 2)$code$C_{G}$[3] and show that it performs almost similar to ML when a parameter$\lambda_{\mathrm{m}\mathrm{m}}$(that determines how far to traverse in the Hasse diagram) is taken to be 3. We also show by simulation that it performs better than a comparable$[8, 5, 2]$linear code under ML decoding.

Motivated by duplex read sequencing developed by Oxford Nanopore Technologies, this paper proposes a concatenated coding scheme for nanopore sequencers where DNA sequences are decoded from noisy reads of the template and reverse-complement strands from the same DNA molecule, that is, a duplex read. First, we show that the double-strand pairwise error probability (PEP) bound is multiplicative with respect to the single-strand PEP bounds of the template and reverse-complement codebooks, thus giving duplex decoders significantly lower error rates compared to simplex decoders which only use the template strand. Then, we propose a decoder for multiple concatenations of short codebooks designed using the double-strand PEP bound.

We generalize the problem of recovering a lost/erased symbol in a Reed-Solomon code to the scenario in which some side information about the lost symbol is known. The side information is represented as a set$S$of linearly independent combinations of the sub-symbols of the lost symbol. When$S=\varnothing$, this reduces to the standard problem of repairing a single codeword symbol. When$S$is a set of sub-symbols of the erased one, this becomes the repair problem with partially lost/erased symbol. We first establish that the minimum repair bandwidth depends on$\vert S\vert$and not the content of$S$and construct a lower bound on the repair bandwidth of a linear repair scheme with side information$S$We then consider the well-known subspace-polynomial repair schemes and show that their repair bandwidths can be optimized by choosing the right subspaces. Finally, we demonstrate several parameter regimes where the optimal bandwidths can be achieved for full-length Reed-Solomon codes.

Abstract In this paper, we focus on the design of binary constant weight codes that admit low-complexity encoding and decoding algorithms, and that have size $$M=2^k$$ M = 2 k so that codewords can conveniently be labeled with binary vectors of length k. For every integer $$\ell \ge 3$$ ℓ ≥ 3 , we construct a $$(n=2^\ell , M=2^{k_{\ell }}, d=2)$$ ( n = 2 ℓ , M = 2 k ℓ , d = 2 ) constant weight code $${{{\mathcal {C}}}}[\ell ]$$ C [ ℓ ] of weight $$\ell $$ ℓ by encoding information in the gaps between successive 1’s of a vector, and call them as cyclic-gap constant weight codes. The code is associated with a finite integer sequence of length $$\ell $$ ℓ satisfying a constraint defined as anchor-decodability that is pivotal to ensure low complexity for encoding and decoding. The time complexity of the encoding algorithm is linear in the input size k, and that of the decoding algorithm is poly-logarithmic in the input size n, discounting the linear time spent on parsing the input. Both the algorithms do not require expensive computation of binomial coefficients, unlike the case in many existing schemes. Among codes generated by all anchor-decodable sequences, we show that $${{{\mathcal {C}}}}[\ell ]$$ C [ ℓ ] has the maximum size with $$k_{\ell } \ge \ell ^2-\ell \log _2\ell + \log _2\ell - 0.279\ell - 0.721$$ k ℓ ≥ ℓ 2 - ℓ log 2 ℓ + log 2 ℓ - 0.279 ℓ - 0.721 . As k is upper bounded by $$\ell ^2-\ell \log _2\ell +O(\ell )$$ ℓ 2 - ℓ log 2 ℓ + O ( ℓ ) information-theoretically, the code $${{{\mathcal {C}}}}[\ell ]$$ C [ ℓ ] is optimal in its size with respect to two higher order terms of $$\ell $$ ℓ . In particular, $$k_\ell $$ k ℓ meets the upper bound for $$\ell =3$$ ℓ = 3 and one-bit away for $$\ell =4$$ ℓ = 4 . On the other hand, we show that $${{{\mathcal {C}}}}[\ell ]$$ C [ ℓ ] is not unique in attaining $$k_{\ell }$$ k ℓ by constructing an alternate code $$\mathcal{{\hat{C}}}[\ell ]$$

The noisy nanopore channel is introduced as a model of the nanopore sequencer in DNA storage that includes inter-symbol interference, sample duplications, and measurement noise. Information rates of the noisy nanopore channel with Markov sources are computed numerically based on a Monte Carlo technique that builds upon existing techniques for finite-state channels. However, the analogous technique for channels with duplications poses a challenging problem from an algorithmic perspective. An approximate algorithm is proposed to compute information rates inO(m√mlog(m)) time with an asymptotically negligible error with respect to block lengthm. Information rates of the nanopore sequencer are studied by choosing parameters of the channel model based on the Scrappie simulator, yielding insights into the fundamental performance of DNA storage systems with nanopore sequencing as the reading process.

We propose a novel supervised dictionary learning framework for text classification, integrating the Lempel-Ziv-Welch (LZW) algorithm for data compression and dictionary construction. This two-phase approach refines dictionaries by optimizing dictionary atoms for discriminative power using mutual information and class distribution. Our method facilitates classifier training, such as SVMs and neural networks. We introduce the information plane area rank (IPAR) to evaluate the information-theoretic performance of our algorithm. Tested on six benchmark text datasets, our model performs nearly as well as top models in limited-vocabulary settings, lagging by only about 2% while using just 10% of the parameters. However, its performance drops in diverse-vocabulary contexts due to the LZW algorithm's limitations with low-repetition data. This contrast highlights its efficiency and limitations across different dataset types.

The design and development of sub-Terahertz (sub-THz) cellular systems entail the need for new channel models that can precisely predict channel characteristics beyond 100GHz in outdoor and dynamic environments. This work proposes a novel multiple-input and multiple-output (MIMO) channel model for cellular communication, developed within the framework of a class of spatio-temporal stochastic processes called ambit-process. The modeling methodology effectively captures the typicalities of sub-THz propagation like molecular absorption and scattering of the evolving multipaths while accounting for the propagation delay of electromagnetic waves across large array apertures deployed at the transmitter and the receiver. This allows for an accurate characterization of the spatial-wideband effect along with other relevant spatio-temporal attributes of the channel. Numerical simulations indicate a good level of agreement between the spectral efficiency and spatio-temporal correlation of the proposed model against a state-of-the-art stochastic Terahertz (THz) channel model and measurements reported in the literature.

The design and development of Terahertz (THz) and sub-Terahertz (sub-THz) communication systems entail the need for new channel models that can precisely predict channel attributes at such frequencies (≥100 GHz) in outdoor and dynamic environments. This work proposes a novel hybrid-stochastic ultra-wideband channel model for sub-THz bands, developed within the framework of a class of spatio-temporal stochastic processes called the ambit-process. The proposed model is capable of supporting bandwidths of upto 1 GHz. The spatio-temporal evolution of the ambit framework allows for a spatially consistent, reasonably accurate and tractable characterization of the fading statistics and multipath propagation of the cellular channels. We leverage a recently proposed convolution-based low-complexity algorithm with necessary modifications to study key features of the microcellular sub-THz channel like associated diffused reflection and scattering, molecular absorption, spatio-temporal correlations, and consistency between the time-evolving delay and Doppler of the multipaths. Simulation results on path loss, shadowing, delay spread, and channel correlations indicate that the ambit model accurately captures the typicalities of an urban microcellular sub-THz channel and agrees well with the measurement results reported in the literature.

In low latency applications and in general, for overspread channels, channel delay spread is a large percentage of the transmission frame duration. In this paper, we consider OTFS in anoverspreadchannel exhibiting a delay spread that exceeds the block duration in a frame, where traditional channel estimation (CE) fails. We propose a two-stage CE method based on a delay-Doppler (DD) training frame, consisting of a dual chirp converted from time domain and a higher power pilot. The first stage employs a DD domain embedded pilot CE to estimate the aliased delays (due to modulo operation) and Doppler shifts, followed by identifying all the underspread paths not coinciding with any overspread path. The second stage utilizes time domain dual chirp correlation to estimate the actual delays and Doppler shifts of the remaining paths. This stage also resolves ambiguity in estimating delays and Doppler shifts for paths sharing same aliased delay. Furthermore, we present a modified low-complexity maximum ratio combining (MRC) detection algorithm for OTFS in overspread channels. Finally, we evaluate performance of OTFS using the proposed CE and the modified MRC detection in terms of normalized mean square error (NMSE) and bit error rate (BER).

Orthogonal time-frequency space (OTFS) modulation shows superior performance in high-mobility wireless environments compared to orthogonal frequency division multiplexing (OFDM). In this paper, we consider maximal ratio combining (MRC) detection for an OTFS receiver with oversampling for channels with fractional delays and Doppler shifts. Specifically, we first reformulate input-output relations in delay-Doppler and delay-time domains for an oversampled OTFS receiver. Then we present a modified iterative MRC detection in both domains taking advantage of the oversampled received signal to improve error performance. The complexity of our detection method is equivalent to that of standard MRC detection scaled by the oversampling factor, while remaining much lower than message passing (MP) detection. We also develop a noise whitening approach to decorrelate the oversampled noise in time domain and derive the optimal combining weights of the MRC detection. Simulation results show that the proposed detection with receiver oversampling outperforms the MRC detection with Nyquist sampling, and the oversampling MP detection. Finally, we show that adding noise whitening can significantly improve error performance, compared to the MRC detection without noise whitening. This comes at a small additional computational cost, while still remaining much lower than MP detection.

We consider the problem of accurately localizing$N$unmanned aerial vehicles (UAV) in 3D space where the UAVs are part of a swarm and communicate with each other through orthogonal time-frequency space (OTFS) modulated signals. Each receiving UAV estimates the multipath wireless channel on each link formed by the line-of-sight (LoS) transmission and by the single reflections from the remaining$N-2$UAVs. The estimated power delay profiles are communicated to an edge server, which is in charge of computing the exact location of the UAVs. To obtain the UAVs locations, we propose an iterative algorithm, named Turbo Iterative Positioning (TIP), which, using the belief-propagation approach, effectively exploits the time difference of arrival (TDoA) measurements between the LoS and the non-LoS paths. Enabling a full cold start (no prior knowledge), our solution first maps each TDoA's profile element to a specific ID of the reflecting UAV's. The localization of the$N$UAVs is then derived via gradient descent optimization, with the aid of turbo-like iterations that can progressively correct some of the residual errors in the initial ID mapping operation. Our numerical results, obtained also using real-world traces, show how the multipath links are beneficial to achieving very accurate localization of all UAVs, even with a limited delay resolution. Robustness of our scheme is proven by its performance approaching the Cramer-Rao bound.

Nanopore sequencing enables reading strings of A,C,G,T nucleotides in DNA strands by pulling them into nanopores with the help of motor proteins. Due to the discrete stepping of motor proteins, the signals produced by a DNA sequence tend to be piecewise-constant expansions of some underlying real-valued sequence. In this paper, we assume that every k-nucleotide sequence corresponds to a real-valued codeword of length$k$, and model the nanopore channel as a noisy duplication channel that stretches every sample of a codeword using a geometric distribution, and then adds Gaussian noise. We show that for this channel, a simpler variant of the dynamic time warping (DTW) algorithm performs maximum likelihood decoding. Next, we devise an$O(k^{2})$- algorithm for bounding the pairwise error probability between two codewords of length$k$. Finally, we use Scrappie to design codebooks with a storage efficiency of 1 bit per nucleotide and demonstrate using error simulations the accuracy of the calculated error bounds.

This paper considers coding schemes for the noisy nanopore channel that models the nanopore sequencer in DNA storage. Our approach involves designing a target Markov source subject to general source constraints, including the homopolymer run-length and GC constraints. We propose a concatenated coding scheme with an inner homophonic code and generic outer error-correction code. The inner code maps binary i.i.d. sources to the target quaternary Markov source by minimising error in the empirical Markov distribution, which measures its "Markov-like" behaviour. This leads to the proposed low-complexity, near-optimal soft decoder for the inner code, demonstrated through numerical results.

In this paper, we calculate a union bound for dynamic time warping (DTW)-based decoding of piecewise constant signals corrupted by additive noise and time stretching due to sample duplications, as observed in raw measurement signals obtained from nanopore sequencers. We consider both finitely- and infinitely-supported duplications with geometric-like characteristic, which include discrete uniform distributions as a special case. First, we provide explicit algorithms that calculate the union bound in O(αk2) time for the infinite-support case and in O(β2k2) for the finite-support case, where k is the codeword length, α is the minimum duplication, and β is the maximum duplication. Next, we show that a multi-read union bound exhibits a thresholding effect, where the error probability can be made arbitrarily close to zero by aggregating DTW distances from sufficiently many independent reads. Finally, we validate the calculated bounds relative to simulation results.

Motivated by the application of Reed-Solomon codes to recently emerging decentralized storage systems such as Storj and Filebase/Sia, we study the problem of designing compact repair groups for recovering multiple failures in a decentralized manner. Here, compactness means that the corresponding trace repair schemes of these groups of helpers can be generated from a single or a few seed repair schemes, thus saving the time and space required for finding and storing them. The goal is to design compact repair groups that can tolerate as many failures as possible. It turns out that the maximum number of failures a collection of repair groups can tolerate equals the size of a minimum hitting set of a collection of subsets of the finite field ${\mathbb{F}_{{q^\ell }}}$ minus one. When the repair groups for each symbol are generated from a single subspace, we establish a pair of asymptotically tight lower bound and upper bound on the size of such a minimum hitting set. Using Burnside’s Lemma and the Möbius inversion formula, we determine a number of subspaces that together attain the upper bound on the minimum hitting set size when the repair groups are generated from multiple subspaces.

Minimum weight codewords play a crucial role in the error correction performance of a linear block code. In this work, we establish an explicit construction for these codewords of polar codes as a sum of the generator matrix rows, which can then be used as a foundation for two applications. In the first application, we obtain a lower bound for the number of minimum-weight codewords (a.k.a. the error coefficient), which matches the exact number established previously in the literature. In the second application, we derive a novel method that modifies the information set (a.k.a. rate profile) of polar codes and PAC codes in order to reduce the error coefficient, hence improving their performance. More specifically, by analyzing the structure of minimum-weight codewords of polar codes (as special sums of the rows in the polar transform matrix), we can identify rows (corresponding to information bits) that contribute the most to the formation of such codewords and then replace them with other rows (corresponding to frozen bits) that bring in few minimum-weight codewords. A similar process can also be applied to PAC codes. Our approach deviates from the traditional constructions of polar codes, which mostly focus on the reliability of the sub-channels, by taking into account another important factor - the weight distribution. Extensive numerical results show that the modified codes outperform PAC codes and CRC-Polar codes at the practical block error rate of$10^{-2}$-$10^{-3}$.

Despite their many successful applications, Deep Neural Networks (DNNs) are vulnerable to intentionally designed adversarial examples. Adversarial robustness describes the ability of a machine learning model, e.g., a neural network, to defend against such adversarial attacks. In coding theory, codebooks are designed to minimize the impact of errors occurring with transmission through a noisy channel. Motivated by the similarities between passing a codeword through a noisy channel and defending against adversarial attacks, Error-Correcting Output Codes (ECOCs) are used to achieve state-of-the-art adversarial robustness. Research on codebook designs and the association of codewords to classification labels (assignment) is still at the very early stages, with great room for improvement. In this work, we present novel codebook design and assignment procedures in two stages due to the complexity (NP-hardness) of the underlying problem. A rule-based heuristic codebook design method is proposed in the first stage and an optimization problem to assign the codewords to labels is proposed in the second stage. Since this optimization is NP-hard, a greedy algorithm is proposed to provide a sub-optimal solution. We demonstrate the effectiveness of our framework on three benchmark datasets, under different types of adversarial attacks. The experimental results show that our error-correcting output code framework can effectively improve the adversarial robustness of machine learning models, with up to a 10% increase in accuracy.

Nanopore sequencing is an emerging DNA sequencing technology that has been proposed for use in DNA storage systems. We propose the noisy nanopore channel model for nanopore sequencing. This model captures duplications, inter-symbol interference, and noisy measurements by concatenating an i.i.d. duplication channel with a finite-state semi-Markov channel. Compared to previous models, this channel models the dominant distortions of the nanopore while remaining tractable. Anticipating future coding schemes, we derive MAP detection algorithms and estimate achievable rates. Given that finite-state semi-Markov channels are a subclass of channels with memory, we conjecture that the achievable rate of the noisy nanopore channel can be optimised using a variation of the generalised Blahut-Arimoto algorithm.

A transaction record in a sharded blockchain can be represented as a two-dimensional array of integers with row-index associated to an account, column-index to a shard and the entry to the transaction amount. In a blockchain-based cryptocurrency system with coded sharding, a transaction record of a given epoch of time is encoded using a maximum-distance-separable code considering the entries as finite-field symbols. Each column of the resultant coded array is then stored in a server. In this paper, we propose a privacy-preserving multi-round protocol that allows a remote client to retrieve from a coded blockchain system the sum of transaction amounts belonging to two different epochs of time, but to the same ac-count. At the core of the protocol lies an algorithm for a remote client to privately compute a non-linear function referred to as integer addition of two finite-field symbols representing integer numbers, in the presence of curious-but-honest adversaries. Applying it to balance-checking in a cryptocurrency system, the protocol guarantees information-theoretic privacy on account number and shard number thereby ensuring perfect user anonymity, and also maintains confidentiality of half of the input bits on average. The protocol turns out to be a useful primitive for balance-checking in lightweight clients of a PolyShard-ed blockchain.

Polar codes are normally constructed based on the reliability of the sub-channels in the polarized vector channel. Code construction based on reliability is compatible with successive cancellation decoding. However, due to poor Hamming distance properties, the designed codes cannot perform well with near maximum likelihood decoders. In this work, we propose a new approach that modifies polar codes and PAC codes to significantly lower the number of codewords with minimum distance (a.k.a. error coefficient). This approach is based on the recognition of all the rows of polar transform involved in the formation of the minimum-weight codewords. The numerical results show that the designed codes outperform polar codes and PAC codes under list decoding.

This paper presents unitary-precoded single-carrier (USC) modulation as a family of waveforms based on multiplexing the information symbols on time domain unitary basis functions. The common property of these basis functions is that they span the entire time and frequency plane. The recently proposed orthogonal time frequency space (OTFS) and orthogonal time sequency multiplexing (OTSM) based on discrete Fourier transform (DFT) and Walsh Hadamard transform (WHT), respectively, fall in the general framework of USC waveforms. In this work, we present channel estimation and detection methods that work for any USC waveform and numerically show that any choice of unitary precoding results in the same error performance. Lastly, we implement some USC systems and compare their performance with OFDM in a real-time indoor setting using an SDR platform.

Constructing efficient low-rate error-correcting codes with low-complexity encoding and decoding has become increasingly important for applications involving ultra-low-power devices such as Internet-of-Things (IoT). To this end, schemes based on concatenating the state-of-the-art codes at moderate rates with repetition codes have emerged as practical solutions deployed in various standards. In this paper, we propose a novel mechanism for concatenating outer polar codes with inner repetition codes which we refer to as polar coded repetition. More specifically, we propose to transmit a slightly modified polar codeword by deviating from Arıkan’s standard$2 \times 2$Kernel in a certain number of polarization recursions at each repetition block. We show how this modification can improve the asymptotic achievable rate of the standard polar-repetition scheme, while ensuring that the overall encoding and decoding complexity is kept almost the same. The achievable rate is analyzed for the binary erasure channel (BEC) and additive white Gaussian noise (AWGN) channel. Moreover, we show that the finite-length performance of the polar coded repetition scheme under cyclic redundancy check (CRC) aided successive cancellation list (SCL) decoder over AWGN channel is better than the uncoded polar-repetition scheme at the cost of a slight increase in decoding complexity. We also compare the proposed scheme, in terms of performance and complexity, with other low-rate solution based on polar codes in the literature.

The successive cancellation (SC) process in which symbols are decoded sequentially by processing some intermediate information is an essential component of various decoding algorithms used for polar codes and their variants. In some decoding schemes, we may need to redo this process from some specific symbol or from the first symbol. This operation is called rewinding. Rewinding the SC process seems trivial if we have access to all intermediate log-likelihood ratios (LLRs) and partial sums. However, as the block length increases, retaining all of the intermediate information becomes inefficient and impractical. Rewinding the SC process in a memory-efficient way is a problem that we address in this paper. As we store a fraction of all the intermediate information in the memory-efficient scheme, we may not be able to rewind the SC process to the target symbol index. The reason is that some of the stored intermediate information needed to decode the target symbol may have been overwritten. To recompute the lost information, we may need to rewind the process further. Before proposing the formal scheme for the rewinding process, we explore the known properties of the SC process based on the binary representation of the bit indices. Then, we introduce a new operator used for grouping the bit indices. This special grouping helps us in finding the closest bit index to the target index for rewinding. We also analytically prove that this approach gives access to the untouched intermediate information stored in the memory which is essential in resuming the SC process. Finally, we adapt the proposed approach to multiple rewinds and apply it to SC-flip decoding and shifted-pruning-based list decoding. The numerical evaluation of the proposed solution shows a significant reduction of ≥50% in the complexity of the additional decoding attempts at medium and high SNR regimes for SC-flip decoding and less for shifted-pruning based list decoding.

Coded delivery has been found to improve content delivery by reducing the data transmitted over a broadcast network. The existing works are mostly theoretical, and do not focus on building coded delivery systems for the wireless edge, especially the WiFi edge. In this paper, we first analyze the potential gains of coded delivery that employs index coding at the WiFi edge. This includes designing a system model and the algorithms therein to study the gains of coded delivery. We also compare the gains due to coding with the gains due to caching. The algorithms include segment coding algorithm at the WiFi AP and a cache replacement policy (LFU-Index) at the end user. The system model is then used as the basis to design and implement Wi-Cache, a coded delivery system at the WiFi edge. Coded delivery in Wi-Cache specifically focuses on improving HTTP based video streaming to WiFi clients. The decoding module at the end user for the coded delivery is implemented as a browser plugin that does not require device side configuration changes. We also present the effect of variable and fixed length video segment size on the perceived performance of video streaming when coded delivery is used.

Concatenating the state-of-the-art codes at moderate rates with repetition codes has emerged as a practical solution deployed in various standards for ultra-low-power devices such as in Internet-of-Things (IoT) networks. In this paper, we propose a novel concatenation mechanism for such applications which need to operate at very low signal-to-noise ratio (SNR) regime. In the proposed scheme, the outer code is a hybrid polar code constructed in two stages, one with a binary kernel and another also with a binary kernel but applied over a binary extension field. The inner code is a non-binary multiplicative repetition code. This particular structure inherits low-complexity decoding structures of polar codes while enabling concatenation with an inner non-binary multiplicative repetition scheme. The decoding for the proposed scheme is done using cyclic redundancy check (CRC) aided successive cancellation list (SCL) decoder over additive white Gaussian noise (AWGN) and Rayleigh fading channels. Simulation results demonstrate that the proposed hybrid non-binary repeated polar code provides performance gain compared to a polar-repetition scheme with comparable decoding complexity.

Concatenating the state-of-the-art codes at moderate rates with repetition codes have emerged as practical solutions deployed in various standards for ultra-low-power devices such as in Internet-of-Things (IoT) networks. In this paper, we propose a novel concatenation mechanism for such applications which need to operate at very low signal-to-noise ratio (SNR) regime. In the proposed scheme, the outer code is a hybrid polar code constructed in two stages, one with a binary kernel and another also with a binary kernel but applied over a binary extension field. The inner code is a non-binary multiplicative repetition code. This particular structure inherits low-complexity decoding structures of polar codes while enabling concatenation with an inner non-binary multiplicative repetition scheme. The decoding for the proposed scheme is done using cyclic redundancy check (CRC) aided successive cancellation list (SCL) decoder over AWGN channel. Simulation results show that the proposed scheme outperforms the straightforward binary polar-repetition scheme at the cost of a negligible increase in the decoding complexity.

In present blockchain systems, privacy of transactions is maintained by keeping the identity of accounts anonymous. The associated pseudonyms are ephemeral in nature, and can not be easily traced back to the real identity. An alternate infallible approach is to make use of private information retrieval (PIR) protocols that enable users to fetch details of transactions without revealing which transactions they seek. In this paper, we formalize this approach for blockchain systems that employ coded sharding. We present a PIR protocol for private data access, in particular private balance-checking, in blockchain systems when data is stored using generalized Reed-Solomon codes. Our protocol can be readily applied to the PolyShard scheme that has been recently proposed as a method to build truly scalable blockchain system.

This paper proposes orthogonal time sequency multiplexing (OTSM), a novel single carrier modulation scheme based on the well known Walsh-Hadamard transform (WHT) combined with row-column interleaving, and zero padding (ZP) between blocks in the time-domain. The information symbols in OTSM are multiplexed in the delay and sequency domain using a cascade of time-division and Walsh-Hadamard (sequency) multiplexing. By using the WHT for transmission and reception, the modulation and demodulation steps do not require any complex multiplications. We then propose two low-complexity detectors: (i) a simpler non-iterative detector based on a single tap minimum mean square time-frequency domain equalizer and (ii) an iterative time-domain detector. We demonstrate, via numerical simulations, that the proposed modulation scheme offers high performance gains over orthogonal frequency division multiplexing (OFDM) and exhibits the same performance of orthogonal time frequency space (OTFS) modulation, but with lower complexity. In proposing OTSM, along with simple detection schemes, we offer the lowest complexity solution to achieving reliable communication in high mobility wireless channels, as compared to the available schemes published so far in the literature.

Non-binary low-density parity-check (NB-LDPC) codes can offer promising performance advantages but suffer from high decoding complexity. To tackle this challenge, in this paper, we consider NB-LDPC codes over finite fields as codes over subfields as a means of reducing decoding complexity. In particular, our approach is based on a novel method of expanding a non-binary Tanner graph over a finite field into a graph over a subfield. This approach offers several decoding strategies for a single NB-LDPC code, with varying levels of performance-complexity trade-offs. Simulation results demonstrate that in a majority of cases, performance loss is minimal when compared with the complexity gains.

Caching content close to the end users, e.g., at cellular base stations (BSs), WiFi access points (APs), and end user devices is known to improve efficiency and effectiveness of content delivery. This motivates the development of caching-as-a-service where edge networks and devices provide storage capacity to content providers, and enable them to strategically populate these caches to improve user experience in the targeted network. In this paper, we describe Wi-Cache, a prototype for providing caching-as-a-service at the WiFi edge. Wi-Cache is an SDN (Software Defined Networking) based distributed content caching system at the WiFi edge that uses storage at the APs for caching content. Wi-Cache caches content on wireless APs and delivers them to mobile clients when they are requested. It allows content providers to have fine-grained control over the AP-caches and also execute efficient content placement and delivery algorithms at the WiFi edge using a set of APIs that are provided by Wi-Cache. We also show the effectiveness of the Wi-Cache system using an extensive set of experiments.

This paper proposesorthogonal time sequency multiplexing (OTSM), a novel single carrier modulation scheme that places information symbols in the delay-sequency domain followed by a cascade of time-division multiplexing (TDM) and Walsh-Hadamard sequence multiplexing. Thanks to the Walsh Hadamard transform (WHT), the modulation and demodulation do not require complex domain multiplications. For the proposed OTSM, we first derive the input-output relation in the delay-sequency domain and present a low complexity detection method taking advantage of zero-padding. We demonstrate via simulations that OTSM offers high performance gains over orthogonal frequency division multiplexing (OFDM) and similar performance to orthogonal time frequency space (OTFS), but at lower complexity owing to WHT. Then we propose a low complexity time domain channel estimation method. Finally, we show how to include an outer error control code and a turbo decoder to improve error performance of the coded system.

NB-LDPC codes, a class of codes well-known for their exceptional error correcting performance, are not yet used widely in practice due to the high complexity of decoding algorithms. In this paper, we propose a low complexity decoder for these codes by means of a novel graph expansion. We view the finite field over which the code is constructed as the quadratic extension of one of its subfields, and then expand the Tanner graph of the code into a graph over that particular field. Decoding algorithm, which is tailored for this larger graph, presents significant complexity gains while the performance loss is minimal.

Constructing efficient low-rate error-correcting codes with low-complexity encoding and decoding have become increasingly important for applications involving ultra-low-power devices such as Internet-of-Things (IoT) networks. To this end, schemes based on concatenating the state-of-the-art codes at moderate rates with repetition codes have emerged as practical solutions deployed in various standards. In this paper, we propose a novel mechanism for concatenating outer polar codes with inner repetition codes which we refer to as polar coded repetition. More specifically, we propose to transmit a slightly modified polar codeword by deviating from Arıkan's standard 2 × 2 Kernel in a certain number of polarization recursions at each repetition block. We show how this modification can improve the asymptotic achievable rate of the polar-repetition scheme, while ensuring that the overall encoding and decoding complexity is kept almost the same. The achievable rate is analyzed for the binary erasure channels (BEC).

The simulation of vehicular wireless channels using geometry-based radio channel models is computationally intensive when the number of scatterers is significantly high. In this paper, we propose a new geometry-based stochastic channel model to simulate and analyze the aforementioned channels based on a framework developed from the theory of ambit processes. Under reasonable assumptions, the underlying mathematical structure of the proposed channel model enables the characterization of high mobility channels in terms of fading statistics, spatiotemporal channel correlation, and Doppler spectrum, besides ensuring tractable analysis. The developed algorithm facilitates fast simulation of high mobility channels and accounts for key features of vehicular channels including appearance and disappearance of multi-path components, spatial consistency, and captures the correlation between time-evolving delay and Doppler associated with multi-path components. Finally, we carry out simulations to obtain crucial insights about the characteristics of typical vehicle-to-infrastructure channels based on the proposed channel model.

This paper presents a linear complexity iterative rake detector for the recently proposed orthogonal time frequency space (OTFS) modulation scheme. The basic idea is to extract and combine the received multipath components of the transmitted symbols in the delay-Doppler grid using linear diversity combining schemes like maximal ratio combining (MRC), equal gain combining and selection combining to improve the SNR of the combined signal. We reformulate the OTFS input-output relation in the vector form by placing some null symbols in the delay-Doppler grid thereby exploiting the block circulant property of the channel matrix. Using the new input-output relation we propose a low complexity iterative detector based on the MRC scheme. The bit error rate (BER) performance of the proposed detector will be compared with the state of the art message passing detector and orthogonal frequency division multiplexing (OFDM) scheme employing a single tap minimum mean square error (MMSE) equalizer. We also show that the frame error rate (FER) performance of the MRC detector can be improved by employing error correcting codes operating in the form of a turbo decision feedback equalizer (DFE).

Staircase codes, a class of product-like codes, have been demonstrated to perform exceptionally well in optical transmission systems. Although they are predominantly used with BCH component codes and hard decision decoding, soft decision decoding has also been recently attempted, with BCH and polar code based staircase codes. We consider using LDPC codes as the component code of soft decoded staircase codes. Results demonstrate that these codes offer very good performance, with gains in the range of 0.5-1dB over soft decoded BCH-staircase codes, at a BER of 1$0^{-8}$. These can be further improved through the novel bit-flipping scheme we propose.

Non-binary low-density parity-check (NB-LDPC) codes are known to offer several advantages over their binary counterparts, but the higher complexity, and the resource-hungry nature of decoding algorithms have so far restricted their practical usage. In this paper, we propose a new decoding algorithm for NB-LDPC codes over finite fields of characteristic 2, based on a novel binary expansion of the Q-ary Tanner graph. While it offers substantial complexity gains, simulation results demonstrate that the performance loss of the new algorithm, in comparison to the best known decoder, is quite small. Furthermore, due to being based on a binary graph, it is particularly attractive for hardware implementations. We also suggest a simplified version of the algorithm, which offers even higher gains in complexity.

In this paper, we develop an orthogonal precoding scheme for integer-forcing (IF) linear receivers using the steepest gradient algorithm. Although this scheme can be viewed as a special case of the unitary precoded integer-forcing (UPIF), it has two major advantages. First, the orthogonal precoding outperforms its unitary counterpart in terms of achievable rate, outage probability, and error rate. We verify this advantage via theoretical and numerical analyses. Second, it exhibits lower complexity as the dimension of orthogonal matrices is half that of unitary matrices in the real-valued domain. For finding “good” orthogonal precoder matrices, we propose an efficient algorithm based on the steepest gradient algorithm that exploits the geometrical properties of orthogonal matrices as a Lie group. The proposed algorithm has low complexity and can be easily applied to an arbitrary MIMO configuration. We also confirm numerically that the proposed orthogonal precoding outperforms UPIF type II in some scenarios and the X-precoder in high-order QAM schemes, e.g., 64- and 256-QAM.

Developing accurate and computationally efficient channel models for mobile wireless channels poses a formidable challenge, primarily due to the highly dynamic nature of such environments and the involvement of a large number of modeling parameters. In this paper, we propose a novel geometrical model to simulate mobile wireless channels based on a framework developed from the theory of ambit processes. Under reasonable assumptions, the underlying mathematical structure of the proposed channel model enables the characterization of mobile wireless channels in terms of fading statistics, spatio-temporal channel correlation, and Doppler spectrum, besides ensuring tractable analysis. Using the ambit process model, we develop an algorithm that enables fast simulation of macro-cellular channels and accounts for key features of such channels including the appearance and disappearance of multi-path components, spatial consistency, and further captures the correlation between time-evolving delay and Doppler associated with multi-path components. Finally, we simulate macro-cellular channels using the proposed algorithm to obtain crucial insights about the channel characteristics. Numerical results indicate that the proposed channel modeling approach serves as a fairly accurate and computationally efficient design framework for wireless communication systems.

This paper focuses on orthogonal precoding for integer-forcing linear receiver and shows it has two advantages over unitary precoding. Orthogonal precoding exhibits lower complexity than unitary precoding because the dimension of orthogonal matrices is half that of unitary matrices for a fixed number of antennas. Moreover, orthogonal precoding outperforms unitary precoding in terms of achievable rate and error-rate. Despite its promising advantages, it is not easy to find the optimal precoding matrices because it involves an orthogonality constraint and the shortest lattice vector problem. To solve this, we separate the optimization problem into two sub-problems and propose methods based on the steepest gradient with Lie groups and a random search algorithm. The proposed methods have low complexity and are applicable to any MIMO dimension. For high-order QAM, the proposed orthogonal precoder outperforms X-precoders which are designed specifically for QAM.

Minimizing the repair bandwidth, i.e., the amount of information from the helper nodes needed for recovering the content of one failed node in an erasure-coded distributed storage system, has been the focus of many works in the literature. We investigate another important performance metric, namely the I/O cost, which specifies the amount of information that needs to be read by the helper nodes during the repair process of one failed node. We analyze the I/O costs of a few known repair schemes for Reed-Solomon codes of various lengths, in contrast to the previous works in this direction, which only studied the I/O costs in repairing full-length Reed-Solomon codes.

Polar codes are constructed based on the reliability of bit-channels. This construction suits the successive cancellation (SC) decoding, where one error in the successive estimation of the bits fails the decoding. However, in SC list (SCL) decoding, the correct path may remain in the list by tolerating multiple penalties. This characteristic of list decoding demands a different approach in code construction. In this work, we modify the conventional construction by a greedy search algorithm in which a bit-swapping approach is employed to re-distribute the low-reliability bits in the subblocks aiming for a reduction in the probability of correct path elimination. The numerical results for polar codes of length 1 kb under CRC-aided SCL decoding show improvements of about 0.4 dB for R=0.8 and over 0.2 dB for R=0.5 at L=32.

A novel iterative approach for soft-decision decoding of Reed-Solomon codes is presented that employs symbol-level belief propagation on an alternative parity-check matrix representation of the code. Construction of a suitable matrix is discussed from the viewpoint of iterative decoding, and certain conditions are derived on existence of structures detrimental for decoding. Simulation results demonstrate that the novel scheme performs substantially better than hard-decision decoding, especially with high rate codes, while being of much lower complexity than existing soft-decision decoding methods. Proposed method is also well-suited for efficient hardware implementations.

In successive cancellation list (SCL) decoding, the list pruning operation retains the L paths with highest likelihoods. However, the correct path might be among the paths with low likelihoods due to channel noise. In this case, the correct path is eliminated from the list. In this work, we study the event of elimination of the correct path and we analyze where and how this event occurs. A modified pruning scheme named shifted-pruning over a set of low-reliability bit-channels named critical bits is proposed aiming to avoid the elimination of the correct path in additional decoding attempts after a decoding failure occurs. Shifted-pruning is realized by selecting the paths k + 1 to k + L out of the 2L ordered paths instead of the paths 1 to L. The numerical results for polar codes of length 512 and code rates 0.5 and 0.8 and list sizes L = 2, 8 and 32 show that the shifted-pruning scheme is a low-complexity equivalent to the bit-flipping scheme while it can outperform the bit-flipping method by providing 0. 25-0.5dB gain.

This paper presents a majority-logic decoding (MLgD) algorithm for non-binary LDPC codes based on a novel expansion of the Tanner graph. The expansion introduced converts the Q-ary graph into a binary one, which makes the new MLgD algorithm more attractive for hardware implementations. Proposed algorithm performs significantly better than the existing MLgD algorithms in the waterfall region, and it shows a much lower error-floor as well. Algorithm only requires integer additions, comparisons, finite field operations and some binary operations. Thus, it offers an effective trade-off between performance and complexity in decoding non-binary LDPC codes.

Vehicle-to-infrastructure (V2I) and vehicle-to- vehicle (V2V) communications find extensive applications, particularly for congestion avoidance and road safety. However, development of such communication systems require accurate modeling of the wireless channel. This paper presents a methodology to simulate cross-road environments involving vehicular traffic. We propose a novel modeling approach for vehicular traffic based on a non-stationary one-dimensional Poisson arrival process which is represented by a M/M/infty queuing model. The joint ray-tracing of the stationary scatterers such as surrounding buildings along with stochastic modeling of mobile scatters such as vehicles reduces simulation time significantly, and yields relevant statistics of channel parameters with a minor compromise in accuracy.

Using an algebraic approach based on the theory of Coxeter groups, we design, and describe the performance of, a class of line codes derived from permutation modulation, useful for parallel transmission of b bits over b + 1 wires, and admitting especially simple encoding and decoding algorithms. With these codes, resistance to common-mode noise is obtained by using codewords whose components sum to zero, simultaneous switching output noise is reduced by using constant-energy signals, and the effects of intersymbol interference are reduced by having decisions based on only two values at the input of the final slicers. Codebook design is based on the theory of Group Codes for the Gaussian Channel, as specialized to Coxeter matrix groups generated by reflections in orthogonal hyperplanes. A number of designs are exhibited, some of them being novel or improving on previously obtained codes.

Multicasting K independent messages via multipleinput multiple-output channels to multiple users where each user already has a subset of messages as side information is studied. A general framework of constructing layered space-time index coding (LSTIC) from a large class of space-time block codes (STBC), including perfect STBC, is proposed. We analyze the proposed LSTIC and show that it provides minimum determinant gains that are exponential with the amount of information contained in the side information for any possible side information. When constructed over a perfect STBC, the proposed LSTIC is itself a perfect STBC and hence many desired properties are preserved. To illustrate, we construct LSTIC over the following wellknown STBCs: Golden code; 3×3, 4×4, and 6×6 perfect STBCs; and Alamouti code. Simulation results show that the obtained side information gain can be well predicted by our analysis.

Multicasting K independent messages via multiple-input multiple-output (MIMO) channels to multiple users where each user already has a subset of messages as side information is studied. A general framework of constructing layered spacetime index coding (LSTIC) from a large class of space-time block codes (STBCs), including perfect STBCs, is proposed. We analyze the proposed LSTIC technique and show that it provides minimum determinant gains that are exponential in the amount of information contained in the side information for any possible side information at the receivers. When constructed over a perfect STBC, the proposed LSTIC is itself a perfect STBC and hence enjoys many desired properties.

Network transfer and disk read constitute the two most time-consuming operations in the repair process for node failures in erasure-code-based distributed storage systems. Recent developments on Reed-Solomon codes have demonstrated repair schemes that achieve optimal network bandwidths in the recovery of single failures, although in certain cases at the expense of a trivially high I/O cost, a term referring to the number of disk reads performed in a repair scheme. We are interested in the lowest I/O cost a repair scheme can achieve for Reed-Solomon codes. We establish two repair schemes for a family of Reed-Solomon codes with two parities that achieve the optimal I/O cost.

Orthogonal time frequency space (OTFS) modulation was shown to provide significant error performance advantages over orthogonal frequency division multiplexing (OFDM) over delay-Doppler channels. The channel impulse response is needed at the receiver to perform OTFS detection. In this work, we analyze OTFS-based channel estimation using a pilot symbol embedded in the data frame: the pilot symbol with a number of guard zero-symbols is suitably located on the delay-Doppler grid containing the information symbols. Different symbol arrangements are proposed depending on whether the channel has integer or fractional Doppler paths relative to an integer grid. The channel information is first estimated from a group of received symbols using a simple threshold method. The estimated information is then used for data detection within the same frame, via a message passing (MP) algorithm. Numerical results compare the error performance of the proposed schemes and the OTFS scheme with ideal channel estimation under similar spectral and energy efficiency. Moreover, our results show that OTFS with non-ideal channel estimation can still outperform OFDM with ideal channel estimation.

This paper develops novel transmission schemes to support secure dual-hop Alice-Ray-Bob relaying communication in the presence of a passive eavesdropper (Eve). Due to unknown eavesdropper channel conditions, data transmissions from Alice (to Ray) and from Ray (to Bob) are required to satisfy the secrecy constraint in terms of maximum acceptable secrecy outage probability (SOP). The throughput maximization problem is studied for two scenarios: 1) fixed (Alice and Ray) power allocation; and 2) adaptive power allocation. The resulting constrained optimization problems are solved using the Lagrangian approach. In each frame, either Alice or Ray or neither can be scheduled for transmission depending on the instantaneous main channel conditions. Numerical results demonstrate the effectiveness of the proposed schemes over the existing schemes under various secrecy constraint and signal-to-noise power ratio (SNR) regimes.

We elaborate on the recently proposed orthogonal time frequency space (OTFS) modulation technique, which provides significant advantages over orthogonal frequency division multiplexing (OFDM) in Doppler channels. We first derive the input-output relation describing OTFS modulation and demodulation (mod/demod) for delay-Doppler channels with arbitrary number of paths, with given delay and Doppler values. We then propose a low-complexity message passing (MP) detection algorithm, which is suitable for large-scale OTFS taking advantage of the inherent channel sparsity. Since the fractional Doppler paths (i.e., not exactly aligned with the Doppler taps) produce the inter Doppler interference (IDI), we adapt the MP detection algorithm to compensate for the effect of IDI in order to further improve performance. Simulations results illustrate the superior performance gains of OTFS over OFDM under various channel conditions.

We consider a dual-hop, decode-and-forward network, where the relay can operate in full-duplex (FD) or half-duplex (HD) mode (X-duplex relay). We model the residual self-interference as an additive Gaussian noise with variance proportional to the relay transmit power, and we assume a Gaussian input distribution at the source. Unlike previous work, we assume that the source is only aware of the transmit power distribution adopted by the relay, but not of the symbols that the relay is currently transmitting. This assumption better reflects the practical situation, where the relay node forwards data traffic but modifies physical-layer or link-layer control information. We then identify the optimal power allocation strategy at the source and relay, which in some cases coincides with the HD transmission mode. We prove that such strategy implies either FD transmissions over an entire time frame or FD/HD transmissions over a variable fraction of the frame. We determine the optimal transmit power level at the source and relay for each frame, or fraction thereof. We compare the performance of our scheme against reference FD and HD techniques, which assume that the source is aware of the symbols instantaneously transmitted by the relay, and show that our solution closely approaches such strategies.

Lattices possess elegant mathematical properties which have been previously used in the literature to show that structured codes can be efficient in a variety of communication scenarios, including coding for the additive white Gaussian noise channel, dirty-paper channel, Wyner-Ziv coding, coding for relay networks, and so forth. We consider the family of single-transmitter multiple-receiver Gaussian channels, where the source transmits a set of common messages to all the receivers (multicast scenario), and each receiver has coded side information, i.e., prior information in the form of linear combinations of the messages. This channel model is motivated by applications to multi-terminal networks, where the nodes may have access to coded versions of the messages from previous signal hops or through orthogonal channels. The capacity of this channel is known and follows from the work of Tuncel (2006), which is based on random coding arguments. In this paper, following the approach of Erez and Zamir, we design lattice codes for this family of channels when the source messages are symbols from a finite field Fpof prime size. Our coding scheme utilizes Construction A lattices designed over the same prime field Fp, and uses algebraic binning at the decoders to expurgate the channel code and obtain good lattice subcodes, for every possible set of linear combinations available as side information. The achievable rate of our coding scheme is a function of the size p of underlying prime field, and approaches the capacity as p tends to infinity.

In this paper, we develop novel transmission schemes for secure dual-hop Alice-Ray-Bob relaying communication over fading channels in the presence of a passive eavesdropper (Eve). To control the risk of secrecy outage under unknown eavesdropper channel conditions, we impose secrecy constraint in terms of maximum allowable secrecy outage probability. We study the throughput-optimal buffer-aided adaptive relaying problem for two scenarios: 1) fixed (Alice and Ray) power allocation and 2) adaptive power allocation. The resulting constrained optimization problems are solved using Lagrangian approach and convex optimization. In each frame, either Alice or Ray or neither is scheduled for transmission depending on the main (Alice-Ray and Ray-Bob) channel conditions. Since the transmission schemes can result in unboundedly large (queuing) delay at Ray's buffer, we next study the transmission schemes guaranteeing the bounded average delay. The optimal transmission problem is formulated as an infinite horizon average reward constrained Markov decision process. Subsequently, by relying on a novel state value function approach, we show that in each frame, the solution can be obtained by solving a concave maximization problem, taking into account both the main channel conditions and the buffer state. An online transmission algorithm is developed to iteratively update the state value function, which converges to the optimal solution without requiring a-priori statistical information on the fading channels. The simulation results demonstrate the effectiveness of the proposed schemes over benchmark schemes under various secrecy constraints and signal-to-noise power ratio regimes.

The recently proposed orthogonal time-frequency-space (OTFS) modulation technique was shown to provide significant error performance advantages over orthogonal frequency division multiplexing (OFDM) over delay-Doppler channels. In this paper, we first derive the explicit input-output relation describing OTFS modulation and demodulation (mod/demod). We then analyze the cases of: 1) ideal pulse-shaping waveforms that satisfy the bi-orthogonality conditions and 2) rectangular waveforms which do not. We show that while only inter-Doppler interference (IDI) is present in the former case, additional inter-carrier interference (ICI) and inter-symbol interference (ISI) occur in the latter case. We next characterize the interferences and develop a novel low-complexity yet efficient message passing (MP) algorithm for joint interference cancellation (IC) and symbol detection. While ICI and ISI are eliminated through appropriate phase shifting, IDI can be mitigated by adapting the MP algorithm to account for only the largest interference terms. The MP algorithm can effectively compensate for a wide range of channel Doppler spreads. Our results indicate that OTFS using practical rectangular waveforms can achieve the performance of OTFS using ideal but non-realizable pulse-shaping waveforms. Finally, simulation results demonstrate the superior error performance gains of the proposed uncoded OTFS schemes over OFDM under various channel conditions.

Using an algebraic approach, we examine the design and the performance of geometrically uniform line coding schemes transmitting b bits over w = b + 1 wires and obtained from a subset of a permutation modulation signal set.

We study the problem of constructing good spacetime codes for broadcasting K independent messages over a MIMO network to L users, where each user demands all the messages and already has a subset of messages as side information. As a first attempt, we consider the 2 × 2 case and propose golden-coded index coding by partitioning the golden codes into K subcodes, one for each message. The proposed scheme is shown to have the property that for any side information configuration, the minimum determinant of the code increases exponentially with the amount of information contained in the side information.

Lattices possess elegant mathematical properties which have been previously used in the literature to show that structured codes can be efficient in a variety of communication scenarios. We consider the family of single-transmitter multiple-receiver Gaussian channels where the source transmits a set of common messages to all the receivers (multicast scenario), and each receiver has coded side information, i.e., prior information in the form of linear combinations of the messages. This channel model is motivated by applications to multi-terminal networks where the nodes may have access to coded versions of the messages from previous signal hops or through orthogonal channels. The capacity of this channel is known and follows from the work of Tuncel (2006), which is based on random coding arguments. In this paper, following the approach introduced by Erez and Zamir, we show that lattice codes are capacity-optimal for this family of channels. The structured coding scheme proposed in this paper is derived from Construction A lattices designed over prime fields, and utilizes algebraic binning at the decoders to expurgate the channel code and obtain good lattice subcodes, for every possible set of linear combinations available as side information.

In multiple-input multiple-output (MIMO) channels with discrete input alphabets, at high signal-to-noise ratio (SNR), maximizing the minimum Euclidean distance (dmin) between all possible received constellation points is known to be the optimal precoding strategy. However, finding the optimal precoder has been proved to be NP-hard. For large MIMO, a promising practical approach is to transform the channel into parallel 2 × 2 MIMO subchannels and then precode each of them separately. However, existing methods are mostly based on heuristic subchannel pairing schemes and require numerical search/optimization in the design phase. In this work, we propose a novel real-valued precoder, named as XY-precoder, which enjoys an explicit construction, a provable dmin, a provably optimal subchannel pairing scheme, and low ML-decoding complexity. We prove that the XY-precoder achieves the same diversity order as the best known precoder, but with a much lower decoding complexity. Simulation results confirm that the error performance of XY-precoder is almost the same as that of the best known precoders.

In this work, we consider a dual-hop, decode-and-forward network where the relay can operate in FD mode. We model the residual self interference as an additive Gaussian noise with variance proportional to the relay transmit power, and we assume a Gaussian input distribution at the source. Unlike previous work, however, we assume that the source is only aware of the transmit power distribution adopted by the relay over a given time horizon, not of the symbols that the relay is currently transmitting. This scenario better reflects practical situations in which the relay node may also have to forward signaling traffic, or data originated by other sources. Under these conditions, we show that the optimal communication strategy that source and relay can adopt is a time-division scheme, and, for each slot, we determine the optimal transmit power level that source and relay should adopt depending on the channel gains. Interestingly, the distribution of the optimal transmit power turns out to be discrete with two probability masses.

Self-coherent orthogonal frequency division multiplexing (OFDM) was introduced to wireless communications as a promising physical layer technique due to its complete immunity against phase noise, simple radio frequency (RF) front-end receiver, and good spectral efficiency achievability. In this paper, we propose an Alamouti coded multiple-input multiple-output (MIMO) self-coherent OFDM and analyze its performance in terms of diversity order. We prove theoretically that the system exhibits a diversity loss due to a doubly fading effect experienced by both the RF carrier and OFDM subcarriers. To compensate this loss, we exploit the smart carrier positioning (SCP) technique in conjunction with the proposed system. We present a novel diversity analysis, which proves the system with SCP approaches full diversity. Finally, we show by simulations that the system with SCP outperforms the other known non-coherent OFDM schemes as well as the conventional MIMO-OFDM, when phase noise presents.

In multiple-input multiple-output (MIMO) fading channels, the design criterion for full-diversity space-time block codes (STBCs) is primarily determined by the decoding method at the receiver. Although constructions of STBCs have predominantly matched the maximum-likelihood (ML) decoder, design criteria and constructions of full- diversity STBCs have also been reported for low- complexity linear receivers. A new receiver architecture called Integer-Forcing (IF) linear receiver has been proposed to MIMO channels by Zhan et al. which showed promising results for the high-rate V-BLAST encoding scheme. In this work we address the design of full-diversity STBCs for IF linear receivers. We derive an upper bound on the probability of decoding error, and show that STBCs that satisfy the non-vanishing singular value (NVS) property provide full-diversity for the IF receiver. We also present simulation results to demonstrate that linear designs with NVS property provide full diversity for IF receiver. As a special case of our analysis on STBCs, we present an upper bound on the error probability for the V- BLAST architecture presented by Zhan et al., and demonstrate that the IF linear receivers provide full receive diversity. Our results supplement the existing outage probability based results for the IF receiver.

We construct error correcting codes for jointly transmitting a finite set of independent messages to an informed receiver which has prior knowledge of the values of some subset of the messages as side information. The transmitter is oblivious to the message subset already known to the receiver and performs encoding in such a way that any possible side information can be used efficiently at the decoder. We construct and identify several families of algebraic error correcting codes for this problem using cyclic and maximum distance separable (MDS) codes. The proposed codes are of short block length, many of them provide optimum or near-optimum error correction capabilities and guarantee larger minimum distances than known codes of similar parameters for informed receivers. The constructed codes are also useful as error correcting codes for index coding when the transmitter does not know the side information available at the receivers.

We consider the problem of oblivious transfer (OT) over OFDM and MIMO wireless communication systems where only the receiver knows the channel state information. The sender and receiver also have unlimited access to a noise-free real channel. Using a physical layer approach, based on the properties of the noisy fading channel, we propose a scheme for honest-but-curious parties that enables the transmitter to send obliviously one-of-two files, i.e., without knowing which one has been actually requested by the receiver, while also ensuring that the receiver does not get any information about the other file.

In this paper, we provide a solution to the open problem of computing the Fourier transform of a binary function defined over n-bit vectors taking m-bit vector values. In particular, we introduce the two-modular Fourier transform (TMFT) of a binary function f : G → ℜ, where G = (F2n, +) is the group of n bit vectors with bitwise modulo two addition +, and ℜ is a finite commutative ring of characteristic 2. Using the specific group structure of G and a sequence of nested subgroups of G, we define the fast TMFT and its inverse. Since the image ℜ of the binary functions is a ring, we can define the convolution between two functions f : G → ℜ. We then provide the TMFT properties, including the convolution theorem, which can be used to efficiently compute convolutions. Finally, we derive the complexity of the fast TMFT and the inverse fast TMFT.

In this paper, we present self-coherent OFDM, a well-known non-coherent technique in optical communications, for wireless RF communications. Self-coherent OFDM is known to have complete immunity against phase noise using a simple RF front-end receiver and to provide a significantly higher spectral efficiency than self-het OFDM, which uses at most 50% of the available spectrum for communications. We present the performance analysis of self-coherent OFDM over additive white Gaussian noise (AWGN) and frequency selective fading channels. We show by simulations that self-coherent OFDM provides not only a higher spectral efficiency but also a better bit error rate (BER) performance than self-het OFDM. Finally, we discuss the impact on the system performance of the filters design parameters used in the self-coherent OFDM receiver.

The Unshared Secret Key Cryptography (USK), recently proposed by the authors, guarantees Shannon's ideal secrecy and perfect secrecy for MIMO wiretap channels, without requiring secret key exchange. However, the requirement of infinite constellation inputs limits its applicability to practical systems. In this paper, we propose a practical USK scheme using finite constellation inputs. The new scheme is based on a cooperative jamming technique, and is valid even if the eavesdropper has more antennas than the transmitter. We show that Shannon's ideal secrecy can be achieved with an arbitrarily small outage probability.

We consider the special case of index coding over the Gaussian broadcast channel where each receiver has prior knowledge of a subset of messages at the transmitter and demands all the messages from the source. We propose a concatenated coding scheme for this problem, using an index code for the Gaussian channel as an inner code/modulation to exploit side information at the receivers, and an outer code to attain coding gain against the channel noise. We derive the capacity region of this scheme by viewing the resulting channel as a multiple-access channel with many receivers, and relate it to the side information gain - which is a measure of the advantage of a code in utilizing receiver side information - of the inner index code/modulation. We demonstrate the utility of the proposed architecture by simulating the performance of an index code/modulation concatenated with an off-the-shelf convolutional code through bit-interleaved coded-modulation.

In this paper we introduce the two-modular Fourier transform of a binary function f : R → R defined over a finite commutative ring R = F2[X]/ϕ(X), where F2[X] is the ring of polynomials with binary coefficients and ϕ(X) is a polynomial of degree n, which is not a multiple of X. We also introduce the corresponding inverse Fourier transform. We then prove the corresponding convolution theorem.

The index coding problem involves a sender with K messages to be transmitted across a broadcast channel, and a set of receivers each of which demands a subset of the K messages while having prior knowledge of a different subset as side information. We consider the specific instance of noisy index coding where the broadcast channel is Gaussian and every receiver demands all the messages from the source. We construct lattice index codes for this channel by encoding the K messages individually using K modulo lattice constellations and transmitting their sum modulo a shaping lattice. We introduce a design metric called side information gain that measures the advantage of a code in utilizing the side information at the receivers, and hence its quality as an index code. Based on the Chinese remainder theorem, we then construct lattice index codes for the Gaussian broadcast channel. Among all lattice index codes constructed using any densest lattice of a given dimension, our codes achieve the maximum side information gain.

We consider the problem of oblivious transfer (OT) over OFDM and MIMO wireless communication systems where only the receiver knows the channel state information. The sender and receiver also have unlimited access to a noise-free real channel. Using a physical layer approach, based on the properties of the noisy fading channel, we propose a scheme that enables the transmitter to send obliviously one-of-two files, i.e, without knowing which one has been actually requested by the receiver, while also ensuring that the receiver does not get any information about the other file.

We introduce cross-packing lattices for Rician fading channels, motivated by a geometric interpretation stemming from the pairwise error probability analysis. We approximate the star bodies arising from the pairwise error probability analysis with n-dimensional crosses of radius t, consisting of 2nt + 1 unit cubes, for some positive integer t. We give a construction for a family of cross-packing lattices for all dimensions and any minimum cross distance 2t + 1. We show by simulations how our new cross-packing lattices perform compared to other known lattices over the Rician fading channel, for different values of the Rician K-factor.

The artificial noise (AN) scheme, proposed by Goel and Negi, is being considered as one of the key enabling technology for secure communications over multiple-output multiple-input wiretap channels. However, the decrease in secrecy rate due to the increase in the number of Eve's antennas is not well understood. In this paper, we develop an analytical framework to characterize the secrecy rate of the AN scheme as a function of Eve's SNR, Bob's SNR, the number of antennas in each terminal, and the power allocation scheme. We first derive a closed-form expression for the average secrecy rate. We then derive a closed-form expression for the asymptotic instantaneous secrecy rate with large number of antennas at all terminals. Finally, we derive simple lower and upper bounds on the average/instantaneous secrecy rate that provide a tool for the system design.

The index coding problem involves a sender with K messages to be transmitted across a broadcast channel, and a set of receivers each of which demands a subset of the K messages while having a prior knowledge of a different subset as side information. We consider the specific case of noisy index coding where the broadcast channel is Gaussian and every receiver demands all the messages from the source. Instances of this communication problem arise in wireless relay networks, sensor networks, and retransmissions in broadcast channels. We construct lattice index codes for this channel by encoding the K messages individually using K modulo lattice constellations and transmitting their sum modulo a coarse lattice. We introduce a design metric called side information gain that measures the advantage of a code in utilizing the side information at the receivers, and hence, its goodness as an index code. Based on the Chinese remainder theorem, we then construct lattice index codes with large side information gains using lattices over the following principal ideal domains: 1) rational integers; 2) Gaussian integers; 3) Eisenstein integers; and 4) Hurwitz quaternions. Among all lattice index codes constructed using any densest lattice of a given dimension, our codes achieve the maximum side information gain. Finally, using an example, we illustrate how the proposed lattice index codes can benefit Gaussian broadcast channels with more general message demands.

While the impact of finite-rate feedback on the capacity of fading channels has been extensively studied in the literature, not much attention has been paid to this problem under secrecy constraint. In this work, we study the ergodic secret capacity of a multiple-input multiple-output multiple-antenna-eavesdropper (MIMOME) wiretap channel with quantized channel state information (CSI) at the transmitter and perfect CSI at the legitimate receiver, under the assumption that only the statistics of eavesdropper CSI is known at the transmitter. We refine the analysis of Lin et al.'s random vector quantization (RVQ) based artificial noise (AN) scheme, where a heuristic upper bound on the secrecy rate loss (compared to the perfect CSI case) was given. We propose a lower bound on the ergodic secrecy capacity. We show that the lower bound and the secrecy capacity with perfect CSI coincide asymptotically as the number of feedback bits and the AN power go to infinity. For practical applications, we propose a very efficient quantization codebook construction method for the two transmit antennas case.

We consider a point-to-point flat-fading MIMO channel with channel state information known both at transmitter and receiver. At the transmitter side, a lattice coding scheme is employed at each antenna to map information symbols to independent lattice codewords drawn from the same codebook. Each lattice codeword is then multiplied by a unitary precoding matrix P and sent through the channel. At the receiver side, an integer-forcing (IF) linear receiver is employed. We denote this scheme as unitary precoded integer-forcing (UPIF). We show that UPIF can achieve full-diversity under a constraint based on the shortest vector of a lattice generated by the precoding matrix P. This constraint and a simpler version of that provide design criteria for two types of full-diversity UPIF. Type I uses a unitary precoder that adapts at each channel realization. Type II uses a unitary precoder, which remains fixed for all channel realizations. We then verify our results by computer simulations in 2×2, and 4×4 MIMO using different QAM constellations. We finally show that the proposed Type II UPIF outperform the MIMO precoding X-codes at high data rates.

In this work, we propose phase precoding for the compute-and-forward (CoF) protocol. We derive the phase precoded computation rate and show that it is greater than the original computation rate of CoF protocol without precoder. To maximize the phase precoded computation rate, we need to `jointly' find the optimum phase precoding matrix and the corresponding network equation coefficients. This is a mixed integer programming problem where the optimum precoders should be obtained at the transmitters and the network equation coefficients have to be computed at the relays. To solve this problem, we introduce phase precoded CoF with partial feedback. It is a quantized precoding system where the relay jointly computes both a quasi-optimal precoder from a finite codebook and the corresponding network equations. The index of the obtained phase precoder within the codebook will then be fedback to the transmitters. A “deep hole phase precoder” is presented as an example of such a scheme. We further simulate our scheme with a lattice code carved out of the Gosset lattice and show that significant coding gains can be obtained in terms of equation error performance.

While information-theoretic security is stronger than computational security, it has long been considered impractical. In this work, we provide new insights into the design of practical information-theoretic cryptosystems. Firstly, from a theoretical point of view, we give a brief introduction into the existing information theoretic security criteria, such as the notions of Shannon's perfect/ideal secrecy in cryptography, and the concept of strong secrecy in coding theory. Secondly, from a practical point of view, we propose the concept of ideal secrecy outage and define a outage probability. Finally, we show how such probability can be made arbitrarily small in a practical cryptosystem.

In cryptography, a shared secret key is normally mandatory to encrypt the confidential message. In this work, we propose the unshared secret key (USK) cryptosystem. Inspired by the artificial noise (AN) technique, we align a one-time pad (OTP) secret key within the null space of a multiple-output multiple-input (MIMO) channel between transmitter and legitimate receiver, so that the OTP is not needed by the legitimate receiver to decipher, while it is fully affecting the eavesdropper's ability to decipher the confidential message. We show that the USK cryptosystem guarantees Shannon's ideal secrecy and perfect secrecy, if an infinite lattice input alphabet is used.

A flat fading point-to-point multiple-antenna channel is considered where the channel state information is known at both transmitter and receiver. At the transmitter side, we use a lattice encoder to map information symbols to lattice codewords. The lattice coded layers are then precoded using unitary matrices satisfying non-vanishing minimum product distance. At the receiver side, an integer-forcing linear receiver is employed. This scheme is called `unitary precoded integer-forcing'. We show that by applying the proposed precoding technique full-diversity can be achieved. We then verify this result by conducting computer simulations in a 2 × 2 and 4 × 4 multiple-input multiple-output (MIMO) channel using full-diversity algebraic rotation precoder matrices.

We consider a new variant of successive cancellation decoder (SCD) for polar codes based on the concept of folding, which was proposed in [1], [2] as technique to reduce the decoding latency at the cost of a higher computational complexity. In this paper, we first formally define the multiple folding operation (iterated κ times), which decomposes the original encoding graph into a number of smaller polar encoding graphs. More specifically, we show that the multiple folding gives rise to a two stage interpretation of the graph representing the polar encoder and the SCD. Based on this, we propose the improved multiple folded successive cancellation decoder (IMFSCD), which combines SCD in one stage and maximum-likelihood decoding in the other. This decoder exhibits a latency gain by a factor of 2κ, still retaining a complexity close to the classic SCD. The small increase in complexity is due to a short maximum likelihood decoder (MLD) used in place of a SCD in the last decoding stage within the IMFSCD. Moreover, we observe by simulation that the decoder performance is exactly the same as that of an SCD at all rates.

Current security techniques can be implemented with either secret key exchange or physical-layer wiretap codes. In this paper, we investigate an alternative solution for MIMO wiretap channels. Inspired by the artificial noise (AN) technique, we propose the unshared secret key (USK) cryptosystem, where the AN is redesigned as a one-time pad secret key aligned within the null space between a transmitter and a legitimate receiver. The proposed USK cryptosystem is a new physical-layer cryptographic scheme, which was obtained by combining traditional network-layer cryptography and physical-layer security. Unlike previously studied AN techniques, rather than ensuring nonzero secrecy capacity, the USK is valid for an infinite lattice input alphabet and guarantees Shannon's ideal secrecy and perfect secrecy without the need for secret key exchange. We then show how ideal secrecy can be obtained for finite lattice constellations with an arbitrarily small outage.

In this paper, we present a subcarrier pairing scheme to improve the overall error performance of self-heterodyne (self-het) OFDM communications. The proposed pairing scheme exploits the average signal-to-interference-to noise ratios (SINRs) imbalance experienced among self-het OFDM subcarriers. At the transmitter, two simple operations, symbol constellation rotation and component interleaving, are performed before pairing the good and the bad OFDM subcarriers, and maximum likelihood detection is used at the receiver to decode the information. The simulation results show that the proposed pairing scheme improves the system performance by 2.5 dB and 0.6 dB for Rayleigh fading and AWGN channels at bit error rate (BER) of 10-3, respectively, without any coding overhead. In addition, we show that, in the presence of phase noise, self-het OFDM using the proposed pairing scheme outperforms the conventional OFDM schemes with superheterodyne receiver structures.

We propose two types of full-rate integer STBCs (ICs) for 2 × 2 Multiple-Input Multiple-Output (MIMO) fading channels. A unique property of ICs is the presence of integer coefficients in the code structure, which enables reduced numbers of processor bits for the encoder. Due to the presence of integer coefficients ICs can be encoded with as low as 3, 5, and 7 bits for 4, 16, and 64-QAM constellations, respectively. We show that ICs are fast Maximum Likelihood (ML) decodable with the worst-case complexity of O(2M2.5) for square M-QAM constellation. We also show that ICs have low Peak-Average-Power-Ratio (PAPR) values. Through computer simulations, we show that ICs outperform the finite-precision versions of the Golden code and the Silver code. Importantly, one of the proposed types of ICs are within a constant gap of 2 dB from the infinite-precision versions of the Golden code and the Silver code for 4, 16, and 64-QAM constellations, at moderate to high SNR values.

The problem of searching the closest lattice point in large dimensional lattices finds many applications in single and/or multiple antenna communications. In this paper, we propose a Gaussian sampling based lattice decoding algorithm (GSLD). The algorithm iteratively updates each coordinate by sampling from a continuous Gaussian distribution and then quantizes the sampled value to the nearest alphabet point. The algorithm complexity per iteration is independent of the size of the alphabet, and hence is of high interest in higher order modulation schemes. We show that the algorithm is able to achieve near-optimal performance in polynomial complexity in different wireless communication system models.

Self-heterodyne OFDM (self-het OFDM) is known to provide complete immunity against frequency-offset and phase noise, with a much lower RF frontend complexity, when compared to conventional OFDM techniques. Self-het OFDM is considered to be a promising physical layer technology for millimeter-wave RF communications, where the implementation of low complexity stable oscillators is technically difficult. Although self-het OFDM has great potential, it has only been studied for additive white Gaussian noise and two-ray channel models. In this paper, we analyze the performance of self-het OFDM for general frequency selective channels and show that the standard self-het OFDM undergoes an outage if the RF carrier is affected by deep fading. In order to avoid this, we introduce a new technique called smart carrier positioning. We show both analytically and by simulation that the smart carrier positioning can improve the diversity order and the performance of standard self-het OFDM by approximately 4dB at bit error rate of 10^{-2}. In addition, we investigate the optimum power allocation between the carrier and the OFDM subcarriers under frequency selective conditions.

We address the application of Barnes-Wall (BW) lattice codes for communication over additive white Gaussian noise (AWGN) channels. We introduce Construction A^prime of complex BW lattices that makes new connection between linear codes over polynomial rings and lattices. We show that Construction A^prime of BW lattices is equivalent to the multilevel construction from Reed-Muller codes proposed by Forney. To decode the BW lattice code, we adapt the low-complexity sequential BW lattice decoder (SBWD) proposed by Micciancio and Nicolosi. First we study the error performance of SBWD for decoding the infinite lattice, and demonstrate that it is powerful in making correct decisions well beyond the packing radius. Subsequently, we use the SBWD to decode lattice codes through a novel noise trimming technique, where the received vector is appropriately scaled before applying the SBWD. We show that the noise trimming technique is most effective for decoding BW lattice codes in smaller dimensions, while the gain diminishes for decoding codes in larger dimensions.

A new architecture called integer-forcing (IF) linear receiver has been recently proposed for multiple-input multiple-output (MIMO) fading channels, wherein an appropriate integer linear combination of the received symbols has to be computed as a part of the decoding process. In this paper, we propose a method based on Hermite-Korkine-Zolotareff (HKZ) and Minkowski lattice basis reduction algorithms to obtain the integer coefficients for the IF receiver. We show that the proposed method provides a lower bound on the ergodic rate, and achieves the full receive diversity. Suitability of complex Lenstra-Lenstra-Lovasz (LLL) lattice reduction algorithm (CLLL) to solve the problem is also investigated. Furthermore, we establish the connection between the proposed IF linear receivers and lattice reduction-aided MIMO detectors (with equivalent complexity), and point out the advantages of the former class of receivers over the latter. For the 2 × 2 and 4× 4 MIMO channels, we compare the coded-block error rate and bit error rate of the proposed approach with that of other linear receivers. Simulation results show that the proposed approach outperforms the zero-forcing (ZF) receiver, minimum mean square error (MMSE) receiver, and the lattice reduction-aided MIMO detectors.

Dense lattice packings can be obtained via the well-known Construction A from binary linear codes. In this paper, we use an extension of Construction A called Construction A' to obtain Barnes-Wall lattices from linear codes over polynomials rings. To obtain the Barnes-Wall lattice BW2min C2mfor any m ≥ 1, we first identify a linear code C2mover the quotient ring Um= F2[u]/umand then propose a mapping ψ : Um→ Z[i] such that the code L2m= ψ (C2m) is a lattice constellation. Further, we show that L2mhas the cubic shaping property when m is even. Finally, we show that BW2mcan be obtained through Construction A' as BW2m= (1 + i)mZ[i]2m⊕ L2m.

Unipolar communications systems can transmit information using only real and positive signals. This includes a variety of physical channels ranging from optical (fiber or free-space), to RF wireless using amplitude modulation with non-coherent reception, to baseband single wire communications. Unipolar OFDM techniques can efficiently compensate frequency selective channel distortion in unipolar communication systems. One of the leading example of unipolar OFDM is asymmetric clipped optical OFDM (ACO-OFDM) originally proposed for optical communications. Flip-OFDM is an alternative approach that was proposed in a patent, but its performance and full potentials have never been investigated in the literature. In this paper, we first compare Flip-OFDM and ACO-OFDM, and show that both techniques have the same performance but different complexities. In particular, Flip-OFDM offers 50% saving in hardware complexity at the receiver over ACO-OFDM. We then propose a new detection scheme, which enables to reduce the noise at the Flip-OFDM receiver by almost 3dB. The analytical performance of the noise filtering schemes is supported by the simulation results.

We consider the root lattice$A_{n}$and derive explicit recursive formulas for the moments of its Voronoi cell. These formulas enable accurate prediction of the error probability of lattice codes constructed from$A_{n}$.

In this paper, we address the design of codes which achieve modulation diversity in block fading single-input single-output (SISO) channels with signal quantization at the receiver. With an unquantized receiver, coding based on algebraic rotations is known to achieve maximum modulation coding diversity. On the other hand, with a quantized receiver, algebraic rotations may not guarantee gains in diversity. Through analysis, we propose specific rotations which result in the codewords having equidistant component-wise projections. We show that the proposed coding scheme achieves maximum modulation diversity with a low-complexity minimum distance decoder and perfect channel knowledge. Relaxing the perfect channel knowledge assumption we propose a novel channel training/estimation technique to estimate the channel. We show that our coding/training/estimation scheme and minimum distance decoding achieves an error probability performance similar to that achieved with perfect channel knowledge.

A novel approach to decode information in a chipless RFID tag using signal space representation (SSR) is presented. SSR represents 2bpossible tag signatures of a b-bit tag as linear combinations of a small set of L orthonormal basis functions. Each signature encoding a binary bit sequence is represented by a point in an L-dimensional constellation. Prototype 3-bit chipless RFID tags are used to validate the detection technique. The proposed method gives a solid mathematical framework to develop detection and decoding methods for more complicated tag reading scenarios.

In this paper, we address the design of codes which achieve modulation diversity in block fading single-input single-output (SISO) channels with signal quantization at receiver and low-complexity decoding. With an unquantized receiver, coding based on algebraic rotations is known to achieve modulation coding diversity. On the other hand, with a quantized receiver, algebraic rotations may not guarantee diversity. Through analysis, we propose specific rotations which result in the codewords having equidistant component-wise projections. We show that the proposed coding scheme achieves maximum modulation diversity with a low-complexity minimum distance decoder.

We consider two uniploar OFDM techniques for optical wireless communications: asymmetric clipped optical OFDM (ACO-OFDM) and Flip-OFDM. Both techniques can be used to compensate multipath distortion effects in optical wireless channels. However, ACO-OFDM has been widely studied in the literature, while the performance of Flip-OFDM has never been investigated. In this paper, we conduct the performance analysis of Flip-OFDM and propose additional modification to the original scheme in order to compare the performance of both techniques. Finally, it is shown by simulation that both techniques have the same performance but different hardware complexities. In particular, for slow fading channels, Flip-OFDM offers 50% saving in hardware complexity over ACO-OFDM at the receiver.

Abstract—We consider a slow fading multiple-input multiple-output (MIMO) system with channel state information at both the transmitter and receiver. A well-known precoding scheme is based upon the singular value decomposition (SVD) of the channel matrix, which transforms the MIMO channel into parallel subchannels. Despite having low maximum likelihood decoding (MLD) complexity, this SVD precoding scheme provides a diversity gain which is limited by the diversity gain of the weakest subchannel. We therefore propose X- and Y-Codes, which improve the diversity gain of the SVD precoding scheme but maintain the low MLD complexity, by jointly coding information across a pair of subchannels. In particular, subchannels with high diversity gain are paired with those having low diversity gain. A pair of subchannels is jointly encoded using a 2 2 real matrix, which is fixed a priori and does not change with each channel realization. For X-Codes, these rotation matrices are parameterized by a single angle, while for Y-Codes, these matrices are left triangular matrices. Moreover, we propose X-, Y-Precoders with the same structure as X-, Y-Codes, but with encoding matrices adapted to each channel realization. We observed that X-Codes/Precoders are good for well-conditioned channels, while Y-Codes/Precoders are good for ill-conditioned channels. Index Terms—Condition number, diversity, error probability, MIMO, precoding, singular value decomposition. I.

We consider Gaussian multiple-input multiple-output (MIMO) channels with discrete input alphabets. We propose a non diagonal precoder based on the X-Codes in to increase the mutual information. The MIMO channel is transformed into a set of parallel subchannels using singular value decomposition (SVD) and X-Codes are then used to pair the subchannels. X-Codes are fully characterized by the pairings and a 2 × 2 real rotation matrix for each pair (parameterized with a single angle). This precoding structure enables us to express the total mutual information as a sum of the mutual information of all the pairs. The problem of finding the optimal precoder with the above structure, which maximizes the total mutual information, is solved by: i) optimizing the rotation angle and the power allocation within each pair and ii) finding the optimal pairing and power allocation among the pairs. It is shown that the mutual information achieved with the proposed pairing scheme is very close to that achieved with the optimal pre coder by Cruz et al., and is significantly better than Mercury/waterfllling strategy by Lozano et al. Our approach greatly simplifies both the precoder optimization and the detection complexity, making it suitable for practical applications.

We consider a time division duplex multiple-input multiple-output (nt× nrMIMO). Using channel state information (CSI) at the transmitter, singular value decomposition (SVD) of the channel matrix is performed. This transforms the MIMO channel into parallel subchannels, but has a low overall diversity order. Hence, we propose X-Codes which achieve a higher diversity order by pairing the subchannels, prior to SVD preceding. In particular, each pair of information symbols is encoded by a fixed 2 × 2 real rotation matrix. X-Codes can be decoded using nrvery low complexity two-dimensional real sphere decoders. Error probability analysis for X-Codes enables us to choose the optimal pairing and the optimal rotation angle for each pair. Finally, we show that our new scheme outperforms other low complexity precoding schemes.

We consider a time division duplex (TDD) nt× nrmultiple-input multiple-output (MIMO) system with known channel state information (CSI) at both transmitter and receiver. Using singular value decomposition (SVD) precoding at the transmitter, the MIMO channels are transformed into parallel subchannels. To improve the low diversity order, we propose X- and Y-Codes, prior to SVD precoding, to pair subchannels having different diversity orders. Specifically, a pair of channels is jointly encoded using a 2 × 2 real matrix, which is fixed a priori and does not change with each channel realization. Moreover, we propose X-, Y-Precoders with the same encoding matrices as X-, Y-Codes, which adapt to each channel realization. The optimal encoding matrices for X- and Y-Codes/Precoders are derived analytically to minimize the average error probability. Finally, we see that X-, Y-Codes/Precoders indeed achieve higher diversity gains at very low encoding/decoding complexity for both well- and ill-conditioned channels, respectively, when compared to other precoding schemes in the literature. We also observe that for the Rayleigh fading channel model X- and Y-Codes/Precoders exhibit the best average error performance.

We consider Gaussian multiple-input multiple-output (MIMO) channels with discrete input alphabets. We propose a non-diagonal precoder based on X-Codes in to increase the mutual information. The MIMO channel is transformed into a set of parallel subchannels using Singular Value Decomposition (SVD) and X-codes are then used to pair the subchannels. X-Codes are fully characterized by the pairings and the 2 × 2 real rotation matrices for each pair (parameterized with a single angle). This precoding structure enables to express the total mutual information as a sum of the mutual information of all the pairs. The problem of finding the optimal precoder with the above structure, which maximizes the total mutual information, is equivalent to i) optimizing the rotation angle and the power allocation within each pair and ii) finding the optimal pairing and power allocation among the pairs. It is shown that the mutual information achieved with the proposed pairing scheme is very close to that achieved with the optimal precoder by Cruz et al., and significantly better than mercury/waterfilling strategy by Lozano et al.. Our approach greatly simplifies both the precoder optimization and the detection complexity, making it suitable for practical applications.

A wireless sensor network with randomly deployed nodes can be used to provide an irregular sampling of a physical field of interest. We assume that a sink node collects the data gathered by the sensors and uses a linear filter for the reconstruction of a bandlimited scalar field defined over a d -dimensional domain. Sensors' locations are assumed to be known at the sink node, up to a certain position error. We then take the mean square error (MSE) of the reconstructed field as performance metric, and evaluate the effect of both uniform and quasi-equally spaced sensor layouts on the quality of the reconstructed field. We define a parameter that provides a measure of the regularity of the sensors deployment, and, through asymptotic analysis, we derive the MSE in the case of different sensor spatial distributions. For two of them, an approximate closed form expression is obtained. We validate our analysis through numerical results, and we show that an excellent match exists between analysis and simulation even for a small number of sensors.

Large MIMO systems represents an effective way to transmit reliably at very high data-rate, but their complexity still represents a problem for practical realization. This paper addresses the hardware implementation of a low-complexity and high-performance detector for a 32 times 32 MIMO. It allows to reach very high data rate, up to more than 170 Mbit/s with a 64 QAM with BER 10-1.5-10-2and constitutes a cost effective improvement over basic detection schemes.

We focus on full-rate, fast-decodable space-time block codes (STBCs) for 2 times 2 and 4times2 multiple-input multiple-output (MIMO) transmission. We first derive conditions and design criteria for reduced-complexity maximum-likelihood (ML) decodable 2times2 STBCs, and we apply them to two families of codes that were recently discovered. Next, we derive a novel reduced-complexity 4times2 STBC, and show that it outperforms all previously known codes with certain constellations.

In this paper, block-coded modulation is used to design a 2 times 2 multiple-input multiple-output (MIMO) space-time code for slow fading channels. The golden code is chosen as the inner code; the scheme is based on a set partitioning of the golden code using two-sided ideals whose norm is a power of two. In this case, a lower bound for the minimum determinant is given by the minimum Hamming distance. The description of the ring structure of the quotients suggests further optimization in order to improve the overall distribution of determinants. Simulation results show that the proposed schemes achieve a significant gain over the un-coded golden code.

The recently proposed Golden code is an optimal space-time block code for 2 times 2 multiple-input-multiple-output (MIMO) systems. The aim of this work is the design of a VLSI decoder for a MIMO system coded with the Golden code. The architecture is based on a rearrangement of the sphere decoding algorithm that achieves maximum-likelihood (ML) decoding performance. Compared to other approaches, the proposed solution exhibits an inherent flexibility in terms of QAM modulation size and this makes our architecture particularly suitable for adaptive modulation schemes. Relying on the flexibility of this approach two different architectures are proposed: a parametric one able to achieve high decoding throughputs (> 165 Mb/s) while keeping low overall decoder complexity (45 KGates), a flexible implementation able to dynamically adapt to the modulation scheme (4-,16-,64-QAM) retaining the low complexity and high throughput features.

The Golden space-time trellis coded modulation (GST-TCM) scheme was proposed for a high rate 2 times 2 multiple-input multiple-output (MIMO) system over slow fading channels. In this letter, we present the performance analysis of GST-TCM over block fading channels, where the channel matrix is constant over a fraction of the codeword length and varies from one fraction to another, independently. In practice, it is not useful to design such codes for specific block fading channel parameters and a robust solution is preferable. We then show both analytically and by simulation that the GST-TCM designed for slow fading channels are indeed robust to all block fading channel conditions.

The deployment of WLAN-based solutions for efficient distribution of multimedia content over wireless links is rapidly increasing in the last few years. Nevertheless many performance issues concerning the delivery of high bit rate stream- oriented content using current IEEE 802.11 standards and the measurements of the customers satisfactions in terms of perceived quality, are still open and of great interest. This paper proposes a simple curve fitting technique for estimating, in a fast and accurate way, the perceived quality of streaming media contents delivered within a wireless network. The model accounts for the effects of various network parameters such as congestion, radio link power and video transmission bit rate. The correctness of the designed model has been verified through many different measurements in realistic wireless environments through an ad-hoc test bed.

We propose an original technique for the design of convolutional Tanner structures that are full diversity under iterative decoding. The code design is based on the analysis of the local trellis neighborhood and is suitable for transmission over wireless non-ergodic channels. This new technique enables us to split the giant convolutional checknode into multiple smaller checknodes which is a means to mimic the standard analysis of LDPC codes under iterative message passing decoding.

In this paper, we first present a modified code-spread code-division multiple-access (CS-CDMA) scheme, named phase-scrambling CDMA (PS-CDMA), for a Gaussian multiple access channel (MAC). In PS-CDMA, we realize the code-spreading using a low-rate serially concatenated code consisting of a convolutional code and a repetition code. Then, we use complex user-specific algebraic-phase scrambling sequences to distinguish users. The receiver is based on the iterative multiuser decoding suggested in [5,8]. Next, we design complex algebraic phase scrambling sequences to mitigate multiple access interferences for overloaded PS-CDMA, i.e., the number of users is greater than the spreading factor. By analyzing extrinsic information transfer (EXIT) curves and the trajectories, we demonstrate that PS-CDMA using the proposed scrambling sequences has faster iterative decoding convergency and better system performance, when compared to the PS-CDMA using random-phase scrambling sequences and some previously known multiple access schemes.

Recently, a family of full-rate, full-diversity space-time block codes (STBCs) for 2 times 2 multiple-input multiple-output (MIMO) channels was proposed in the works of Tirkkonen et al., using a combination of Clifford algebra and Alamouti structures, namely twisted space-time transmit diversity code. This family was recently rediscovered by Paredes et al., and they pointed out that such STBCs enable reduced-complexity maximum-likelihood (ML) decoding. Independently, the same STBCs were found in the work of Samuel and Fitz (2007) and named multi-strata space-time codes. In this paper we show how this code can be constructed algebraically from a particular cyclic division algebra (CDA). This formulation enables to prove that the code has the non-vanishing determinant (NVD) property and hence achieves the diversity-multiplexing tradeoff (DMT) optimality. The fact that the normalized minimum determinant is 1/radic(7) places this code in the second position with respect to the golden code, which exhibits a minimum determinant of 1/radic(5), and motivates the name silver code.

We consider a block coded modulation scheme for a 2 times 2 MIMO system over slow fading channels, where the inner code is the Golden Code. The scheme is based on a set partitioning of the Golden Code using two-sided ideals. A lower bound for the minimum determinant is given by the minimum Hamming distance. Performance simulations show that our GCRS schemes achieve a significant gain over the uncoded Golden Code.

In this paper, we consider multiuser space-time block codes (STBCs) for 2times2 multiple-input multiple-output (MIMO) uplink transmissions. Using a truncated union-bound (UB) approximation, we propose design criteria of multiuser STBCs for quasi-static fading MIMO multiple access channels (MACs). Next, we demonstrate how, by combining the structure of algebraic perfect STBCs in [10], a family of multiuser STBCs can be constructed to fulfill the design criteria, and show that the proposed STBC outperforms all previously known codes over quasi-static fading MIMO MACs.

Exactly determining the geographical position of a telecommunication device is an open research challenge for the personal and mobile communications community. In this paper we explore the terminal localization problem in a GSM system, and we develop a set of carrier independent solutions. Specifically, we introduce four different techniques, all based on the 6-strongest cells traditionally used in the GSM standard. Through extensive simulations we show that our technique can achieve remarkable results without requiring any additional equipment in the core network or the mobile devices.

In this paper we study wireless sensor networks for monitoring applications. We focus on the problem of sampling and reconstruction of multidimensional bandlimited signals, when the sensor locations are equally spaced points affected by some jitter, and the sensor measurements are affected by noise. We show how the mean square reconstruction error can be estimated from the eigenvalue distribution of a certain Toeplitz matrix. We analyze the d-dimensional case, and we show how the mean square error can be easily estimated by using asymptotic analysis.

We study the error probability performance of rotated lattice constellations in frequency-flat Nakagami-m block-fading channels. In particular, we use the sphere lower bound on the underlying infinite lattice as a performance benchmark. We show that the sphere lower bound has full diversity. We observe that optimally rotated lattices with largest known minimum product distance perform very close to the lower bound, while the ensemble of random rotations is shown to lack diversity and perform far from it.

We consider the problem of obtaining a high quality estimates of band-limited sensor fields when sensor measurements are noisy and the nodes are irregularly deployed and subject to random motion. We consider the mean square error (MSE) of the estimate and we analytically derive the performance of several reconstruction/estimation techniques based on linear filtering. For each technique, we obtain the mean value of the MSE, as well as its asymptotic expression in the case where the field bandwidth and the number of sensors grow to infinity, while their ratio is kept constant. Our results provide useful guidelines for the design of sensor networks when many system parameters have to be traded off.

alessandro.nordio © polito.it chiasserini © polito.it viterbo © deis.unical.it ABSTRACT The irregular sampling theory is concerned with the problem We consider wireless sensor networks whose nodes are randomly of recovering a bandlimited signal from a sequence of samples, deployed and, thus, provide an irregular sampling of the sensed which may be taken in an irregular way. Several reconstruction field. The field is assumed to be bandlimited; a sink node col- algorithms have been proposed in the literature (see e.g., [1]) and lects the data gathered by the sensors and reconstructs the field by have found application in a variety of fields, such as digital medical using a technique based on linear filtering. By taking the mean imaging [2,3], geophysics [4], weather forecast [5], astronomy, and square error (MSE) as performance metric, we evaluate the effect oceanography [6]. of quasi-equally spaced sensor layouts on the quality of the recon-Recently, a great deal of attention has been devoted to sensor netstructed signal. The MSE is derived through asymptotic analysis works, whose nodes sample a physical field, like air temperature, for different sensor spatial distributions, and for two of them we light intensity, pollution levels or rain falls, and report the data to are able to obtain an approximate closed form expression. The case a common processing unit (sink node). The sink node is in charge of uniformly distributed sensors is also considered for the sake of of reconstructing the sensed field. In general, sensors are not regcomparison. The validity of our asymptotic analysis is shown by ularly deployed in the area of interest and, if not synchronized to

Golden space-time trellis coded modulation (GST-TCM) scheme was proposed in [1] for a high rate 2times2 multiple- input multiple-output (MIMO) system over slow fading channels. In this paper, we present the design criteria of GST-TCM over general block fading channels, where the channel matrix is constant over a fraction of the codeword length and varies from one fraction to another independently. However, the code construction and optimization can be difficult to implement. We therefore analyze the performance of GST-TCM for slow fading over block fading channels. The impact of the block fading channel on the code performance is analyzed using a truncated Union Bound technique. We finally show both analytically and by simulation that the GST-TCM designed for slow fading channels are indeed robust to various channel conditions. This feature is particularly useful for transmission over multipath channels using multicarrier modulation such as OFDM.

In this paper, we present a multidimensional trellis coded modulation scheme for a high rate 2times2 multiple-input multiple-output (MIMO) system over slow fading channels. Set partitioning of the Golden code is designed specifically to increase the minimum determinant. The branches of the outer trellis code are labeled with these partitions and Viterbi algorithm is applied for trellis decoding. In order to compute the branch metrics, a sphere decoder is used. The general framework for code design and optimization is given. Performance of the proposed scheme is evaluated by simulation and it is shown that it achieves significant performance gains over the uncoded Golden code

In this paper, we consider the downlink of a space time block coded multiuser multiple-input multiple-output (MIMO) system. We propose a transmission scheme to support highest possible data rate and full diversity for multiuser MIMO systems. For this, threaded algebraic space-time block codes and perfect space-time block codes are employed. Different spreading matrices are used to separate the data streams of multiple users. After despreading the signal sequence at the receiver of each user, the maximum likelihood decoding is obtained by a lattice decoder. Performance of the multiuser MIMO system in the presence of multiple access interference is evaluated by simulations in terms of block error rate

We study the error probability performance of rotated lattice constellations in frequency-flat block-fading channels. In particular, we use the sphere lower bound on the underlying infinite lattice as a performance benchmark. We show that the sphere lower bound has full diversity. We observe that optimally rotated lattices with largest known minimum product distance perform very close to the lower bound, while the ensemble of random rotations is shown to lack diversity and perform far from it. We furthermore use the bound in the multiple-antenna case, and we observe that the Golden code, the optimal full-rate full-diversity 2x2 space-time block code, is also very close to the lower bound.

In this work, we give a bound on performance of any full-diversity lattice constellation constructed from algebraic number fields. We show that most of the already available constructions are almost optimal in the sense that any further improvement of the minimum product distance would lead to a negligible coding gain. Furthermore, we discuss constructions, minimum product distance, and bounds for full-diversity complex rotated Z[i]/sup n/-lattices for any dimension n, which avoid the need of component interleaving.

In this paper, we introduce the notion of perfect space-time block codes (STBCs). These codes have full-rate, full-diversity, nonvanishing constant minimum determinant for increasing spectral efficiency, uniform average transmitted energy per antenna and good shaping. We present algebraic constructions of perfect STBCs for 2, 3, 4, and 6 antennas

The major contribution of this paper is the computation of an accurate approximation of the symbol error probability of multidimensional signal constellations used for transmission over independent Rayleigh fading channels. Here we attempt to compute the exact error probability and show how some apparently rather gross approximations still lead to an accurate result

In this paper, the Golden code for a 2/spl times/2 multiple-input multiple-output (MIMO) system is presented. This is a full-rate 2/spl times/2 linear dispersion algebraic space-time code with unprecedented performance based on the Golden number 1+/spl radic/5/2.

In this work, we give a bound on performance of any full-diversity lattice constellation constructed from algebraic number fields. We show that most of the already available constructions are almost optimal in the sense that any further improvement of the minimum product distance would lead to a negligible coding gain.

In this paper we present the Golden code for a 2times2 MIMO system. This is a full-rate 2times2 linear dispersion algebraic space-time code with unprecedented performance based on the Golden number 1+radic5/2

In this paper, we present a novel mathematical investigation on the dispersion-limited optical communication channel. We tackle the problem using a comprehensive approach that is based on the optimization of the energy transfer from the input to the output of the channel. We solve the optimization problem deriving a fundamental integral equation, which we are able to solve analytically. We show that the dispersion-limited optical channel has a very interesting equivalence to the ideal lowpass filter. This equivalence allows us to derive new bounds on the maximum achievable bit rate on the channel with limited intersymbol interference (ISI). In particular, we demonstrate that by suitably increasing the memory of the modulator and using the optimal pulses derived in this paper, one can transmit with limited ISI over a channel with arbitrarily high dispersion.

In this correspondence, we present various families of full diversity rotated Z/sup n/-lattice constellations based on algebraic number theory constructions. We are able to give closed-form expressions of their minimum product distance using the corresponding algebraic properties.

We present new algebraic constructions of rotated cubic lattice constellations of prime dimension based on cyclic fields. The resulting constellations have full diversity and can be ranked according to the minimum product distance, a relevant performance parameter for transmission over the Rayleigh fading channel.

In this paper, we deal with dynamic pricing strategies for connection-oriented services in wireless systems. Dynamic pricing policies allow the network operator to charge a cost per time unit depending on the network usage. In this way, the users behavior can be regulated and the network management is significantly improved. We model the user demand and the call duration as functions of the service price. By using standard Markovian techniques to represent the system evolution, we devise an optimal linear pricing scheme, which can be easily computed and controlled. When compared with a flat-rate policy, where a constant price for the network services is fixed, the proposed solution is able to provide a better quality of service to the users as well as a greater revenue to the network operator. For example, when eight radio channels are available and the traffic load is equal to 0.8, we obtain a 25% improvement in the network revenue with respect to the flat-rate policy, while the blocking probability is halved.

We study the performance of a UNITS downlink, as achieved by a single-user (RAKE) and a multiuser (linear MMSE) receiver with adaptive modulation and multicode in the presence of multipath fading. We advocate an adaptive transmission scheme that varies the number of virtual users and the modulation spectral efficiency in order to optimize the system throughput. Two multipath channel models are considered, exhibiting 3 and 9 paths, respectively. Over the more favorable multipath channel, the multiuser MMSE receiver yields a significant performance enhancement with respect to the RAKE receiver.

Using asymptotic analysis, we study the effect of frequency-flat fading on code division multiple access (CDMA) systems with linear receivers and random spreading sequences. Specifically, we let the number of users grow without bound, while the ratio of number of users to spreading sequence length is kept fixed to a value /spl alpha/. We treat separately the cases of slow fading (nonergodic channel) and of fast fading (ergodic channel). For the former channel, we derive the outage probability, while for the latter we compute the channel capacity. In both cases, multiple classes of users with different qualities of service are dealt with. As /spl alpha//spl rarr//spl infin/, the system throughput tends to the same limit of 1.44 bit/symbol as for the nonfading channel with both single-user matched filter (SUMF) and linear minimum mean-square-error (MMSE) receivers. The outage probability exhibits a floor for all /spl alpha/ with the SUMF receivers, while with MMSE receiver the floor is present only for /spl alpha/>1. We also address the tradeoffs involved in the allocation of available bandwidth between spreading and coding.

We study signal-space coding for coherent slow frequency-hopped communications over a Gaussian multiple-access collision channel (G-MACC). We define signal sets and interleavers having maximum collision resistance. The packet-error probability and the spectral efficiency obtained by these signal sets concatenated with outer block coding and hard (error-only) decoding is evaluated without assuming perfect interleaving. Closed-form expressions are provided and computer simulations show perfect agreement with analysis. The structure of good interleavers is also discussed. More generally, we present expressions for the information outage probability and for the achievable (ergodic) rate of the G-MACC at hand, under various assumptions on user coding and decoding strategies. The outage probability yields the limiting packet-error probability with finite interleaving depth (delay-limited systems). The achievable rate yields the limiting system spectral efficiency for large interleaving depth (delay-unconstrained systems). Comparisons with other classical multiple-access schemes are provided.

Given an abstract group /spl Gscr/, an N-dimensional orthogonal matrix representation G of /spl Gscr/, and an "initial vector" x/spl isin/R/sup N/, Slepian defined the group code generated by the representation G to be the set of vectors Gx. If G is a group of permutation matrices, the set Gx is called a "permutation code". For permutation codes a "stack algorithm" decoder exists that, in the presence of low noise, produces the maximum-likelihood estimate of the transmitted vector by using far fewer computations than the standard decoder. In this correspondence, a new concept of equivalence of codes of different dimensions is presented which is weaker than the usual definition of equivalent codes. We show that every group code is (weakly) equivalent to a permutation code and we discuss the minimal degree of this permutation code.

Maximization of the energy transfer ratio for time-limited signals over linear channels is considered. The case of linear channels with rational transfer function is addressed and a general procedure for the analytic solution of the maximization problem is outlined. The maximum energy transfer ratio over a fixed time interval is evaluated in some cases of interest. Two performance metrics-the energy transfer ratio and the energy intersymbol interference (ISI) ratio-are evaluated for optimal signals and compared to those of commonly used rectangular and sinusoidal pulses in order to determine the achievable gain.

We analyze Z/sub 4/S- and Z/sub 9/-linear lifts of the binary [24, 12] and ternary [12, 6]-Golay code under different weight functions on the underlying ring, and present algebraic decoding schemes for these codes.

We present a maximum-likelihood decoding algorithm for an arbitrary lattice code when used over an independent fading channel with perfect channel state information at the receiver. The decoder is based on a bounded distance search among the lattice points falling inside a sphere centered at the received point. By judicious choice of the decoding radius we show that this decoder can be practically used to decode lattice codes of dimension up to 32 in a fading environment.

The increasing need for high data-rate transmissions over time- or frequency-selective fading channels has drawn attention to modulation schemes with high spectral efficiency such as QAM. With the aim of increasing the "diversity order" of the signal set we consider multidimensional rotated QAM constellations. Very high diversity orders can be achieved and this results in an almost Gaussian performance over the fading channel, This multidimensional modulation scheme is essentially uncoded and enables one to trade diversity for system complexity, at no power or bandwidth expense.

Following the approach introduced by Cavers and Ho (1992), the performance of component-interleaved multidimensional constellations over the Rayleigh fading channel is evaluated analytically. The error probabilities are approximated by the union bound using an exact expression of the pairwise error probability. Simulation results show that this bound can be used effectively as a design criterion for the selection of high-diversity multidimensional constellation over the Rayleigh fading channel.

Recent work on lattices matched to the Rayleigh fading channel has shown how to construct good signal constellations with high spectral efficiency. We present a new family of lattice constellations, based on complex algebraic number fields, which have good performance on Rayleigh fading channels. Some of these lattices also present a reasonable packing density and thus may be used at the same time over a Gaussian channel. Conversely, we show that particular versions of the best lattice packings (D/sub 4/, E/sub 6/, E/sub 8/, K/sub 12/, /spl Lambda//sub 16/, /spl Lambda//sub 24/), constructed from totally complex algebraic cyclotomic fields, present better performance over the Rayleigh fading channel. The practical interest in such signal constellations rises from the need to transmit information at high rates over both terrestrial and satellite links. Some further results in algebraic number theory related to ideals and their factorization are presented and the decoding algorithm used with these lattice constellations are illustrated together with practical results.

Numerical evaluation of some typical lattice parameters such as density, thickness, dimensionless second moment (quantizing constant), etc., are considered. Computational complexity grows exponentially with the dimension of the lattices and all known results rely on the very regular structure of some of these. In the paper the authors present a general algorithm which enables computation of all the common parameters for any given lattice by means of a complete description of its Voronoi cell. Using this algorithm, they have computed previously unknown values of the quantizing constants of some particularly interesting lattices. These results can be used to evaluate the performance of lattice quantizers and lattice signal constellations for the Gaussian channel. As an application they evaluate a tight upper bound for the error probability of a lattice constellation used for transmission over the additive white Gaussian noise channel.