Considerando a possível adoção de tecnologias MIMO (Multiple Input Multiple Output) para a radiodifusão de televisão digital em resolução 8K, esta dissertação parte de experimentos com um sistema de transmissão MIMO OFDM (Otrhogonal Frequency Division Multiplexing) 4096 QAM (Quadrature Amplitude Modulation) em ambiente urbano. Os dados experimentais permitem comparar as atenuações medidas nas polarizações horizontal e vertical, no que se observa pequenas diferenças. De forma a contribuir com projetos de tais sistemas, a cobertura de sistemas de radiodifusão, os dados experimentais são empregados para otimizar (sintonizar) os parâmetros do modelo de propagação ITU R-P.1546; para isso, utiliza-se os métodos gradiente descendente e Newton-Raphson de forma a encontrar o conjunto de parâmetros que minimiza o erro médio quadrático entre a perda de percurso prevista pelo modelo e a medida. Essa otimização é realizada nas polarizações horizontal e vertical isoladamente e conjuntamente. Como resultado obtêm-se conjuntos de parâmetros que conferem maior acurácia ao modelo ITU R-P.1546. A seguir, considera-se o projeto de cobertura de redes de frequência única (SFN - Single Frequency Network). Propõe-se um algoritmo heurístico para obter posições de estações que permitam cobrir uma região de interesse com uma intensidade mínima de sinal. A cobertura obtida é avaliada e heurísticas são empregadas para buscar por configurações do sistema, a alocação das localizações das antenas da SFN, que melhorem o desempenho. As heurísticas consideram informações de relevo e a sobreposição de coberturas entre diferentes estações transmissoras. O algoritmo proposto é iterativo e como resultado final fornece uma quantidade de transmissores e suas localizações de forma a atender uma região satisfazendo um patamar de intensidade de sinal. Assim, esta dissertação aborda aspectos que permitem facilitar projetos de sistemas de radiodifusão, principalmente de SFNs, na faixa de UHF. Os resultados são bastante promissores, pois a otimização dos parâmetros do modelo ITU R-P.1546 melhora a acurácia da predição de cobertura do mesmo e a heurística proposta permite obter posições candidatas para a implementação de SFNs, para posterior survey.

This paper considers a cooperative bistatic scenario for integrated sensing and communication (ISAC) paradigm, where transmitter and receiver base stations (BS) are connected through the front-haul to a central unit (CU), enabling cooperation. A multiple-input multiple-output (MIMO) configuration is considered in combination with orthogonal frequency division multiplexing (OFDM). The communication and radio-sensing functions are performed in orthogonal sets of sub-carriers, where the sub-carriers allocated to radio-sensing are distributed among antennas in an interleaved way. The interleaved frame structure is exploited in the design of a new parameter estimation method. The proposed method is a two-stage algorithm to estimate the delay/Doppler shift and angular position of objects (paths) in the channel. First, the multiple signal classification (MUSIC) algorithm estimates the angle-of-arrival (AoA) of the paths. Then, the delay, Doppler shift and angle-of-departure (AoD) are jointly estimated for each AoA combining an extended search over the AoD domain and a two-dimensional periodogram. The simulations show that the delay, Doppler shift and AoA are estimated correctly, while the estimation of the AoD may report error, although it can be compensated.

This paper studies the performance of the quasi-orthogonal Tirkkonen spatial-frequency block code (SFBC) for integrated sensing and communication (ISAC) scenarios. The considered scenario is a MIMO monostatic ISAC base station (BS), where transmitter and radar antenna arrays are co-located enabling the virtual array concept. The quasi-orthogonal Tirkkonen SFBC is encapsulated in an OFDM waveform, the radar processing is performed over the resulting OFDM frame. The performance in terms of radar and communication metrics of Tirkkonen SFBC is presented and compared with orthogonal Alamouti SFBC and the spectrally interleaved waveform approach, widely used in radar-like scenarios. The resulting Mean Square Error (MSE) of the Angle of Arrival (AoA) is chosen as the radar metric while the bit-error-rate (BER) is used to present the communication performance. The results show that Tirkkonen is a good candidate for future ISAC scenarios.

The integrated sensing and communication (ISAC) paradigm is being proposed for 6G as a new feature of the physical layer (PHY), for tackling dual-functional applications, i.e., demanding radio-sensing and communication functions, such as the Internet of Things (IoT) and autonomous driving systems. This work considers the integration of sensing and communications functionalities in a unique platform. To achieve this goal, the use of orthogonal space frequency block codes (SFBC) is proposed. SFBC code orthogonality enables both the separation of communications data streams at a user terminal and the estimation of target parameters. The SFBC enhances the communications link diversity without requiring channel state information knowledge at the transmitter and enable the virtual antenna array concept for enhancing the direction-finding resolution. The use of different SFBCs provides a tradeoff between achieved diversity and sensing resolution. For example, an Alamouti code, applicable for the case with two transmitting antennas, duplicates sensing resolution and achieves a diversity order of two while the use of a Tarokh code, applicable for a scenario with four transmitting antennas, provides a fourfold better resolution and diversity order of four. However, the code rate achieved with the Tarokh code is half of the one achieved with the Alamouti code. Furthermore, the unambiguous range is reduced since the bandwidth is divided to multiplex the different antenna signals. For its simplicity, good performance and reduced integration requirements, the method is promising for future ISAC systems.

Future generation communication systems are aiming to provide a tremendous high data rate with low-latency high reliable and three-dimensional coverage. To achieve such a challenging goal, it is required to have very precise location information related to the mobile terminal. The advancement of signal processing techniques and communication technologies enables the path for improving localization performance. Recently, intelligent reflecting surface (IRS) has been widely considered as the key element for the future generation of wireless communication. Over the past few years, the performance of IRS-assisted networks is extensively investigated from the point of view of communication purposes and its improvement. However, by virtue of its potential, IRS finds its application for wireless localization. In this paper, we discuss and summarize the works that have already been carried out targeting localization performance improvement. In addition, we figured out the associated challenges and the opportunities to scale up the localization accuracy. Particularly in this paper, the authors have discussed the challenging issues such as channel modeling, channel estimation, system architecture, hardware impairment, IRS deployment strategies, phase optimization, mobility management, and near-field environments. Although these challenges are associated with opportunities to make the IRS-assisted system more effective and efficient.

5G technology represented a major breakthrough in the field of telecommunications because, among other innovations, it made it possible to communicate on frequencies that had never been used before, such as the millimeter wave band. These waves have very high speeds, but they also have some disadvantages, such as the inability to overcome obstacles and high signal losses. To solve this problem, massive MIMO technology is used, which involves the use of a large number of antennas. This approach not only maintains high information transfer rates, but also improves spectral efficiency. However, due to the large number of antennas involved in massive MIMO, it is essential that each antenna carries out directional transmissions to avoid interference between them. This requires the use of beam management, which led 3GPP to develop standards to carry out this management effectively. During this process, the best beams are selected at both the transmitter and receiver, and for this it is necessary to know the characteristics of the channel. To facilitate this process, a parameter called “Rank Indicator” is used, which indicates the number of independent channels in a data stream. This dissertation focuses on this parameter, as the aim is to develop an efficient algorithm to calculate the channel rank for 5G networks and then submit it to the OpenAirInterface repository, since the users of this platform are corrently limited to communicating with a maximum channel rank of two. OpenAirInterface is an open source 5G platform based on the implementation of the technologies defined by 3GPP, and its software can be used for both academic and industrial environments. The development of its software covers both the core network, the access network, and devices. As will be presented in this document, the algorithm developed is not only capable of calculating the Rank Indicator for larger channels, but also improves execution times compared to the existing algorithm of OpenAirInterface in 2x2 MIMO systems. A test over the air with a commercial device is also shown in this document to verify the efficiency of the algorithm in a real scenario.

The aim of this paper is to propose and evaluate multiuser linear precoding techniques for downlink of multicell MIMO based networks. We consider a high-speed backhaul network where the base stations are transparently linked by optical fiber to a central unit. This architecture allows an efficient joint multicell multiuser processing. The proposed precoder is designed in two phases: first the intercell interference is removed by applying a block diagonalization algorithm. Then the system is further optimized by proposing three power allocation algorithms with per-BS power constraint and different complexity tradeoffs: one optimal to minimize the BER and two suboptimal. The performance of the proposed schemes is evaluated, considering typical pedestrian scenarios based on LTE specifications. Numerical results show that the proposed suboptimal power allocation schemes achieve a performance close to the optimal. © 2011 IEEE.

This paper deals with a new multi-user linear precoding technique for downlink of distributed MIMO OFDM systems. We consider a distributed broadband wireless system where some base stations are transparently linked by optical fiber to a central unit. We further assume that the user terminals are equipped with an antenna array and the distributed base stations equipped with either single or an antenna array. This architecture provides a high speed backhaul channel allowing an efficient joint multi-cell processing. The proposed power allocation algorithm is based on minimization of the sum of inverse signal-to-noise ratio (SNR-1) on each user terminal over the available subcarriers. The motivation to minimize the sum of SNR-1 instead of bit error rate (BER) is in the fact that the first criterion achieves a closed-form solution, which is more interesting from practical point of view. The aim is to propose a practical distributed precoding technique to remove the inter-cell interference and improve the user's fairness at the cell-edges. The performance of the proposed scheme is evaluated, considering typical pedestrian scenarios based on LTE specifications.

In this paper, we consider a multiuser distributed MIMO system, under multipath fading channels, with orthogonal frequency division multiplexing (OFDM) technology. The aim is to extend and evaluate, co-located precoding schemes that have been recently proposed, in a distributed scenario. Assuming knowledge of CSI prior to transmission, we can remove the interference among users by employing precoding schemes for the downlink. We assessed closed form and iterative schemes based on block diagonalization (BD) to improve the performance of the distributed antenna system. The results show that the iterative scheme outperforms the closed one. The simulation results show that the studied schemes can be efficient for distributed MIMO OFDM based systems.

In this paper we propose and asses multiuser linear precoding techniques for the downlink of distributed MIMO OFDM systems. We consider a distributed broadband wireless system where the base stations are transparently linked by optical fiber to a central unit. We further assume that both the distributed base stations and the user terminals are equipped with an antenna array. This architecture provides a high speed backhaul channel allowing an efficient joint multiuser multicell processing. The precoder is designed in two phases: first the intercell interference is removed by applying a block diagonalization algorithm. Then the system is further optimized by using a new power allocation algorithm, based on minimization of the sum of inverse signal-to-noise ratio (SNR−1) on each user terminal over the available subcarriers. The motivation to minimize the sum of SNR−1 instead of bit error rate is the fact that the first criterion achieves a closed-form solution, which is more interesting from practical point of view. The aim is to propose a practical distributed precoding technique to remove the intercell interference and improve the user’s fairness at the cell-edges. The performance of the proposed scheme is evaluated and compared with an iterative precoding scheme designed to minimize the bit error rate, extended to the proposed multiuser distributed scenario, considering typical pedestrian scenarios based on LTE specifications.