Novel networking paradigms based on programmability and softwarization are deeply transforming the architecture and end-to-end management of next-generation mobile networks. This demonstration provides a step beyond in this transformation process by showcasing the full cloud-native deployment of a disaggregated and distributed 5 G mobile network from core to Radio Access Network (RAN) using open-source software. The distinguishing features of the proposed approach are that the orchestration process includes the use of a cloud-based Distributed Unit (DU) communicating through O-RAN Split 7.2 with a Radio Unit (RU) performing over-the-air transmission, the end-to-end configuration of slices with on-demand activation of core network function components, and the dynamic configuration of transport network flows to differently route the traffic of active slices.

This work considers the problem of estimating the distance between two covariance matrices directly from the data. Particularly, we are interested in the family of distances that can be expressed as sums of traces of functions that are separately applied to each covariance matrix. This family of distances is particularly useful as it takes into consideration the fact that covariance matrices lie in the Riemannian manifold of positive definite matrices, thereby including a variety of commonly used metrics, such as the Euclidean distance, Jeffreys’ divergence, and the log-Euclidean distance. Moreover, a statistical analysis of the asymptotic behavior of this class of distance estimators has also been conducted. Specifically, we present a central limit theorem that establishes the asymptotic Gaussianity of these estimators and provides closed form expressions for the corresponding means and variances. Empirical evaluations demonstrate the superiority of our proposed consistent estimator over conventional plug-in estimators in multivariate analytical contexts. Additionally, the central limit theorem derived in this study provides a robust statistical framework to assess of accuracy of these estimators.

The problem of estimating the distance between two covariance matrices is considered. A general estimator is provided for a class of metrics, the estimator of which has never been addressed before in the literature. This corresponds to distances that can be expressed as sums of traces of functions that are separately applied to each covariance, which is the case of multiple covariance distances recently derived by Riemannian geometry considerations. The proposed family of estimators is shown to be consistent when both the sample size and the observation dimension increase to infinity at the same rate. In particular, a closed form expression is derived for an estimator of the log-Euclidean metric between covariance matrices. Numerical evaluations demonstrate the effectiveness of this estimator even in relatively small dimensional settings.

A methodology to cluster multiple sets of Gaussian multivariate complex observations based on the alignment of their column spaces is presented. These subspaces are identified with points in the Grassmann manifold and compared according to a similarity measure drawn from a chosen manifold distance, which is proportional to the squared projection–Frobenius norm. In order to guarantee that distances between subspaces of different dimensions are comparable, we proposed to normalise the corresponding decision statistics with respect to their asymptotic mean and variance, assuming that (i) the dimensions of both the observation and the involved subspaces are large but comparable in magnitude and (ii) both subspaces are generated by the same statistical law. A procedure is derived to estimate these normalisation parameters, leading to a new statistic that can be built exclusively from the observations. The method is applied to a MIMO wireless channel clustering problem, where is shown to outperform conventional similarity measures in terms of classification performance.

In this paper, a simple equalization strategy for OFDM waveforms is proposed that specifically targets the case where the cyclic prefix is insufficient to span the whole channel duration. The proposed architecture can be very efficiently implemented in the frequency domain without the need for complex matrix inversions or iterative estimation procedures. Furthermore, the equalizer is shown to outperform conventional methodologies as the system dimensions grow large. Numerical results confirm the excellent behavior of the proposed strategy even for conventional values of the system size.

The performance of short block length codes in the presence of multi-variate stationary Rayleigh fading coherent channels is studied. The channel model is inspired by multi-symbol OFDM transmissions for ultra-reliable low latency communication (URLLC) services, according to which information is sent in a small number of OFDM symbols to reduce latency. More specifically, the dispersion of the coherent fading channel is generalized from the scalar case, which is well known in the literature, to the multivariate one. The obtained expressions are then particularized to the Rayleigh fading statistics and expressed in closed form as a series expansion. Finally, a high SNR approximation of the ergodic capacity and channel dispersion is derived for this particular fading choice. Results show that the code performance depends on the time-frequency fading correlation through very simple functions of the channel correlation coefficients. In particular, it is shown that the channel dispersion converges to a constant plus the sum of the dilogarithms of the correlation coefficients of the channel process. These formulas provide a very useful tool to design physical layer system parameters from channel correlation information measured at the receiver.

An underdetermined multi-measurement vector linear regression problem is considered where the parameter matrix is row-sparse and where an additional constraint fixes the number of nonzero elements in the active rows. Even if this additional constraint offers side structure information that could be exploited to improve the estimation accuracy, it is highly nonconvex and must be dealt with with caution. A detection algorithm is proposed that capitalizes on compressed sensing results and on the generalized distributive law (message passing on factor graphs).

The problem of eigenvector precoding for multi-stream MIMO transmission with filterbank multicarrier (FBMC) modulations is considered. The transmitter is assumed to use a different precoding matrix for each subcarrier, which is constructed by selecting some eigenvectors of the channel matrix. Surprisingly, the phase ambiguity that is inherent to the definition of the eigenvectors turns out to have a crucial effect on the system performance under strong channel frequency selectivity. This is due to the inherent lack of orthogonality of FBMC modulations in these situations. It is shown that by properly selecting the reference phase evolution of each eigenvector across the transmission bandwidth, the global performance of the system can be significantly improved. A phase reference construction strategy is presented that minimizes an upper bound on the total intersymbol/intercarrier interference (ISI/ICI) power.

The problem of MIMO transmission using filterbank multicarrier (FBMC) modulations in strong frequency selective channels is considered. A novel architecture for the implementation of MIMO precoders and linear receivers is derived, which consists of multiple parallel stages that are combined at the per-subcarrier level. Each of these stages is constructed like a classical FBMC modulator/demodulator, using the successive derivatives of the prototype pulse instead of the original one. The performance of the proposed architecture is theoretically characterized in terms of the residual distortion power at the output of the receiver, assuming an asymptotically large number of subcarriers. Results demonstrate the effectiveness of the proposed architecture in MIMO channels with severe frequency selectivity.

A point-to-point multiple-relay communication system with half-duplex constraints is considered. The relays operate under the amplify-and-forward paradigm and implement a linear dispersion distributed space-time code with randomized dispersion matrices of independent and identically distributed entries. The large-signal-to-noise-ratio behavior of the asymptotically large deterministic system is studied for both the optimum (maximum likelihood) receiver and the linear minimum mean squared error (LMMSE) receiver. The diversity order of the system is shown to have a strong dependence on the aspect ratio of the linear dispersion matrices. More specifically, when the linear dispersion matrices are sufficiently tall, both receivers achieve the maximum diversity order, i.e., the total number of relays plus one. Conversely, when the linear dispersion matrices are fat (in the sense that relays linearly compress the information received from the source), the optimum receiver is shown to achieve an asymptotic diversity order of two, whereas the LMMSE receiver is totally unable to exploit the available spatial diversity.

A simple half-duplex decode-and-forward relay channel is presented and analyzed. Relays access the common channel by means of a randomized linear-dispersion space-time block code which is flexible with respect to the number of relays and the coding rate α. When the dimensions of the linear dispersion matrices grow large, but with constant ratio α, the spectral efficiency of the system converges fast to a deterministic quantity. Simulation results show that this asymptotic value is an extremely good approximation of the finite reality, even for not-so-large codes. Then, this asymptotic spectral efficiency is used to characterize the outage probability in the high-SNR regime. With maximum-likelihood reception, the proposed randomized coding scheme is shown to achieve full diversity order L+1, with L the total number of relays. On the contrary, with the sub-optimal LMMSE receiver, relays add diversity to the system only if the coding rate is small enough.

This paper considers a cooperative communications system where a single relay aids a point-to-point transmission using an amplify and forward configuration. The relay linearly encodes the K received symbols into N new ones by means of a matrix multiplication, and the destination employs a LMMSE filter to estimate the information originally transmitted. A large- SNR approximation of the outage probability Poutis derived for this system. The analysis of Poutshows that the diversity order of the system depends on the ratio K/N: if such a ratio is too high (the relay excessively compresses the information), no diversity is added by introducing the relay. Conversely, if this ratio is smaller than a certain quantity, diversity order 2 is ensured. The derived expressions are finally used to establish the diversity-multiplexing tradeoff of the system.

This paper analyzes a cooperative communications system where a set of decode and forward relays provides support to a point to point communication. Each relay linearly transforms the K received symbols, if correctly decoded, into N new ones to be sent to the destination. The coding matrices are randomly generated, making the system simple to design, scalable and robust to synchronism errors. It is shown that such a random code, together with the optimal maximum-likelihood receiver, achieves full diversity for any value of the ratio alpha = K/N. This is not true for the linear minimum mean square error receiver, which loses diversity when alpha increases beyond a given threshold. To avoid dealing with the randomness of the code, the analysis is carried out in the asymptotic domain, i.e. for K and N growing without bound but with ratio converging to a finite quantity alpha. Random matrix theory results are used to derive this asymptotic approximation.

We present in this paper the analytical evaluation of a simple mechanism to reduce the average transmission delay of master stations in a network based on the Distributed Queuing MAC protocol for Ad hoc Networks (DQMAN). When DQMAN is executed, the network is self-organized into dynamic and spontaneous master-slave clusters. Within each cluster, a high performance MAC protocol based on a tree-splitting collision resolution algorithm which uses access minislots is executed. By allowing temporary master stations to avoid contention to get access to the channel, their average packet transmission delay can be effectively reduced compared to that of slaves. This technique provides thus master stations with higher access priority to the channel and, indeed, could be used in any MAC protocol based on access minislots to provide a subset of users with higher priority.

This paper presents a communication system where point-to-point transmissions are aided by L half-duplex, amplify and forward relays which access a common channel by means of random spreading matrices. During the relaying phase, the source can either remain silent or send new symbols. The two cases are compared in terms of spectral efficiency, showing that the latter is always preferable. Next, a sufficient condition for the superiority of the presented relaying scheme over the simple direct-link channel is derived. Particularizing to the one relay case, this condition turns out to be also necessary and allows to identify which is the best time-sharing strategy between relay receiving and transmitting phases. We conclude the paper by discussing the suboptimal linear-minimum-mean-square-error receiver, which is known to be the linear filter that guarantees the maximum signal to noise and interference ratio at its output. To avoid dealing with the randomness introduced by the spreading matrices, the analysis is carried out in the asymptotic regime, i.e. when letting the number of transmitted symbols and the signature length grow without bound but with constant ratio. Under these hypotheses, indeed, random matrix theory results show that it is possible to derive deterministic almost sure equivalents which are excellent approximations of the finite reality.

This paper considers a relay communication system where cooperative diversity is achieved by spreading the relay transmissions using direct-sequence CDMA (DS/CDMA). We derive expressions for the signal to noise ratio (SNR) employing different receiver filters. The relay signatures are generated according to a random model and the SNR is evaluated in the asymptotic domain, assuming that the number of relays and the signature length grow without bound but with constant ratio. We will also see how the introduction of the signatures, together with the use of the linear minimum square error receiver, effectively transform the relay channel in a set of parallel connections, thus fully exploiting cooperative diversity.