This paper considers the problem of beam alignment in a cell-free massive MIMO deployment with multiple access points (APs) and multiple user equipments (UEs) simultaneously operating in the same millimeter wave frequency band. Assuming the availability of a control channel at sub-6 GHz frequencies, a protocol is developed that permits estimating, for each UE, the strongest propagation path from each of the surrounding APs, and to perform user-centric association between the UEs and the APs. Estimation of the strongest paths from nearby APs is realized at the UE in a one-phase procedure, during which all the APs simultaneously transmit on pseudo-randomly selected channels with pseudo-random transmit beamformers. An algorithm for orthogonal channels assignment to the APs is also proposed, with the aim of minimizing the mutual interference between APs that transmit on the same channels. The performance of the proposed strategy is evaluated both in terms of probability of correct detection of the directions of arrival and of departure associated to the strongest beam from nearby APs, and in terms of downlink and uplink signal-to-interference-plus-noise ratio. Numerical results show that the proposed approach is effective and capable of efficiently realizing beam alignment in a multi-UE multi-AP wireless scenario.

The problem of beam alignment (BA) in a cell-free massive multiple-input multiple-output (CF-mMIMO) system operating at millimeter wave (mmWaves) carrier frequencies is considered in this paper. Two estimation algorithms are proposed, in association with a protocol that permits simultaneous estimation, on a shared set of frequencies, for each user equipment (UE), of the direction of arrival and departure of the radio waves associated to the strongest propagation paths from each of the surrounding access points (APs), so that UE-AP association can take place. The proposed procedure relies on the existence of a reliable control channel at sub-6 GHz frequency, so as to enable exchange of estimated values between the UEs and the network, and assumes that APs can be identifies based on the prior knowledge of the orthogonal channels and transmit beamforming codebook. A strategy for assigning codebook entries to the several APs is also proposed, with the aim of minimizing the mutual interference between APs that are assigned the same entry. Numerical results show the effectiveness of the proposed detection strategy, thus enabling one shot fast BA for CF-mMIMO systems.

Wireless connectivity is rapidly becoming ubiquitous and affordable. As a consequence, most wireless devices are nowadays equipped with multi-connectivity, that is, availability of multiple radio access technologies (RATs). Each of these RATs has different characteristics that can be suitably utilized for different connectivity tasks. For example, a long-range low-rate RAT can be used for topology management and coordination, whereas a short-range high-rate RAT for data transmission. In this paper, we introduce a distributed consensus protocol for the hierarchical organization of Wireless Mesh Networks (WMNs) with devices using multiple RATs. Our protocol considers three hierarchical roles after the initial setup: Master, cluster head (CH), and cluster member (CM). The Master coordinates the use of all RATs, whereas the CHs coordinate all but the RAT with the longest transmission range. The initial setup takes place immediately after powering on the devices, after which the devices self-organize in a distributed manner by means of a consensus to elect the Masters and CHs. The resulting interconnected structure is based on the connectivity graphs created with the different RATs. The distributed consensus protocol operates with a minimal amount of network information and demonstrates high networking performance.

Reconfigurable Intelligent Surfaces (RISs) are recently attracting a wide interest due to their capability of tuning wireless propagation environments in order to increase the system performance of wireless networks. In this paper, a multi-user single-cell wireless network assisted by a RIS is studied. First of all, for the special case of a single-user system, three possible approaches are shown in order to optimize the Signal-to-Noise Ratio with respect to the beamformer used at the base station and to the RIS phase shifts. Then, for a multi-user system, assuming channel-matched beamforming, the geometric mean of the downlink Signal-to-Interference plus Noise Ratios across users is maximized with respect to the base stations transmit powers and RIS phase shifts configurations. Numerical results show that the proposed procedures are effective and greatly improve the performance of the system.

Millimeter-wave (mmWave) communication is envisioned to be a promising technology to cater for the continuous growth of wireless communication capacity demand. To compensate severe path loss for mmWave signals, mmWave system typically employs beamforming technique to achieve essential antenna gain. To provide services to multiple user equipment (UE), mmWave system needs to schedule UEs in both frequency and beam domain to achieve optimal target utility function. To this end, this paper proposes an efficient joint beam-frequency scheduling algorithm to achieve target scheduling metric while possessing reasonable complexity. As the results of the scheduling algorithm, multiple UEs are optimally multiplexed in both frequency and beam domains in terms of target scheduling metric.

mmMAGIC (Millimetre-Wave Based Mobile Radio Access Network for Fifth Generation Integrated Communications) is an EU funded 5G-PPP project, whose overall objective is to design and pre-develop a mobile radio access technology (RAT) operating in the 6–100 GHz range, capable of impacting standards and other relevant fora. The focus of the project is on extreme Mobile Broadband, which is expected to drive the 5G requirements for massive increase in capacity and data-rates. This paper elaborates on some 5G key research areas such as: identification of the most compelling use-cases and Key Performance Indicators (KPIs) for future 5G systems, advantages and challenges of millimeter-wave (mmWave) technologies, channel measurements and channel modeling, network architecture; and the design of a new mobile radio interface including multi-node and multi-antenna transceiver architecture.

We present a general scheme for the lossy transmission of a source with arbitrary statistics through a noisy channel under the mean-square error fidelity criterion. Our approach is based on transform coding, scalar quantization of the transform coefficients and linear encoding of the quantization indices. Entropy coding and channel coding are merged into a single linear encoding function, such that the ¿catastrophic¿ behavior of conventional entropy coding is avoided and the full power of modern coding techniques and iterative ¿Belief-Propagation¿ decoding can be exploited. We show that this approach is asymptotically optimal in the limit of large block length, for arbitrary source statistics and binary-input output-symmetric channel. In the practical regime of finite block length and low decoding complexity, we show, through the explicit construction of codes for the lossy transmission of digital images over a binary symmetric channel, that our approach yields significant improvements with respect to previously proposed channel-optimized quantization schemes and also with respect to the conventional concatenation of state-of-the art image coding with state-of-the art channel coding. Although our constructive example focuses on a special case, the approach is general and can be applied to other classes of sources of practical interest.

The multicasting of an independent and identically distributed Gaussian source over a binary erasure broadcast channel is considered. This model applies to a one-to-many transmission scenario in which some mechanism at the physical layer delivers information packets with losses represented by erasures, and users are subject to different erasure probabilities. The reconstruction signal-to-noise ratio (SNR) region achieved by concatenating a multiresolution source code with a broadcast channel code is characterized and four convex optimization problems corresponding to different performance criteria are solved. Each problem defines a particular operating point on the dominant face of the SNR region. Layered joint source-channel codes are constructed based on the concatenation of embedded scalar quantizers with binary raptor encoders. The proposed schemes are shown to operate very close to the theoretical optimum.

In this paper the multicasting of independent parallel Gaussian sources over a binary erasure broadcast channel is considered. Multiresolution embedded quantization and layered joint source-channel coding schemes are used in order to serve simultaneously several users at different channel capacities. The convex nature of the rate-distortion function, computed by means of reverse water-filling, allows us to solve relevant convex optimization problems corresponding to different performance criteria. Then, layered joint source-channel codes are constructed based on the concatenation of embedded scalar quantizers with binary rateless encoders.

In this paper a scheme for joint source-channel coding based on low-density-parity-check (LDPC) codes is investigated. Two concatenated independent LDPC codes are used in the transmitter: one for source coding and the other for channel coding, with a joint belief propagation decoder. The asymptotic behavior is analyzed using EXtrinsic Information Transfer (EXIT) charts and this approximation is corroborated with illustrative experiments. The optimization of the degree distributions for our sparse code to maximize the information transmission rate is also considered.

Interest in distributed source coding (DSC) has increased in recent years due to the development of wireless networks. In this paper we propose a solution based on a new rateless class of codes, the Raptor codes. In real applications (where the data source length and the correlation between the sources may vary), rateless codes can be naturally adapted by generating just a single codeword with suitable length. Raptor codes were already considered by Caire et al. (2005) for the lossless compression of a single source.

In this paper, we describe a method for fast determination of distortion-based optimal unequal error protection (UEP) of bitstreams generated by embedded image coders and transmitted over memoryless noisy channels. The UEP problem is reduced to the more general problem of finding a path in a graph, where each path of the graph represents a possible protection policy, with the objective of selecting the best path being that one inducing minimal distortion. The problem is combinatorially complex and excludes a brute force approach. The solution is provided by applying heuristic information from the problem domain to reduce search complexity. In particular, we use graph search procedure A suggested by Hart , well known in the field of artificial intelligence, to avoid exhaustive search. Numerical results show that this technique outperforms the method presented by Hamzaoui , in terms of Mean Square Error (MSE) distortion and computational complexity. After testing our solution using analytical models of the operational distortion curves proposed by Charfi , we implement a transmission architecture that, using the actual distortion values generated by a real embedded coder, computes the optimal protection policy for the considered image, protects the packets, and transmits them over a channel.

In this paper the problem of distributed source coding (DSC) of binary sources with side information at the decoder is addressed. We propose a scheme based on Raptor codes which are a new class of rateless codes. We adapt the decoding scheme to this problem by implementing the message passing strategy between the constituent decoders of Raptor codes at each decoding iteration. The proposed approach enables to achieve better performances than those achieved by the solutions based on turbo codes, and by the solutions based on regular low density parity check codes (LDPC) codes.

A method for the fast determination of distortion-based optimal unequal error protection (UEP) of bitstreams generated by embedded image coders is described. The UEP problem is reduced to the more general problem of finding a path in a graph, where each path of the graph represents a possible protection policy and the best path is that one inducing minimal distortion. The problem is combinatorially complex and excludes a brute force approach. The solution is provided by applying heuristic information from the problem domain to reduce search complexity. In particular, we use graph search procedure A, well known in the field of artificial intelligence, to avoid exhaustive search. Numerical results show that this technique outperforms the methods presented in [1], [2], in terms of mean square error (MSE) distortion and computational complexity.

In this paper, a joint source channel coding scheme for error resilient image transmission is proposed. Instead of compressing the image using the classical entropy coder, the redundancy of the image is exploited by using turbo codes for both data compression and error protection. At the decoder, the bit-planes are reconstructed in sequence by a multistage decoder. By properly choosing rate and puncturing, the system is able to approach the limit theoretically attainable and to outperform the separated approach of a JPEG2000 compressed image and the best turbo codes for the same overall length.

The recent growth in personal wireless communication devices being used for image transmission, have poised a challenge to protect this data against loss over mobile radio channels. The paper addresses this problem investigating error protection schemes in the context of JPEG2000 compressed imagery. More particularly, the results reported in this paper provide coding guidelines concerning the selection of appropriate turbo code parameters along with optimized JPEG2000 error resilience tools.

This paper proposes a novel approach to energy efficient data transmission based on radio link estimation and adaptive channel coding. A channel protection algorithm is proposed to achieve efficient transmission (in terms of bit error rate), while reducing as much as possible power consumption and transmission bandwidth. The algorithm has been implemented and integrated within an experimental set-up based on a narrowband "ad hoc" network. It has been evaluated through field trials carried out in a hilly region with terrain characteristics that reproduce a variety of situations. The adopted simplified propagation model is based on the well-known knife-edge approximation while the radio link budget is computed by the mobile terminals thanks to 3D map information locally available. The level of channel protection is adaptively matched to the estimated radio link by tuning the transmission parameters and by configuring the Reed-Solomon protection code. Theoretical background and preliminary experimental results are presented in detail.