MIMO for Mobile Satellite Digital Broadcasting: From Theory to Practice

Byman, Aaron; Hulkkonen, Ari; Arapoglou, Pantelis-Daniel; Bertinelli, Massimo; Gaudenzi, R. De

doi:10.1109/tvt.2015.2462757

Cited by 21 publications

(8 citation statements)

References 22 publications

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“…It is noted that (35) may also be used to evaluate uncorrelated STPLD systems, or STPLD systems with either transmit-side or receive-side correlation. To model a system with no transmit-side correlation, C Tx is set to a 2N Tx × 2N Tx identity matrix in (26). Similarly, to model a system with no receive-side correlation, C Rx is set to a 2N Rx × 2N Rx identity matrix in (26).…”

Section: Correlated Error Performancementioning

confidence: 99%

A multiple‐input, multiple‐output broadcasting system with space, time, polarization, and labeling diversity

Patel

Quazi

2022

Trans Emerging Tel Tech

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Enhancing the reliability of wireless links plays an important role in addressing the digital divide between under-developed and developed nations. Diversity techniques are used in wireless communication to improve link reliability. This article presents a broadcasting system that incorporates space, time, polarization and labeling diversity. The key challenge in incorporating labeling diversity into a system is the design of appropriate bit-to-symbol mappers. The latest technique to designing bit-to-symbol mappers is to use a genetic algorithm approach, which is applicable to any generic modulation scheme. This article presents a modified genetic algorithm mapper design algorithm based on recent advances in labeling diversity evaluation theory. The proposed system is studied under ideal (uncorrelated) conditions, as well as in the presence of inter-beam and inter-antenna inference (correlated conditions). Analytical expressions are presented to model both the correlated and uncorrelated systems, and are verified via Monte Carlo simulations. When compared to the best comparable scheme at a bit-error-rate of 10 −6 , results show that the proposed system improves performance by ≈7 dB for a 2 × 2 16APSK system configuration, and by ≈5 dB for both 2 × 4 32APSK and 2 × 2 64APSK system configurations.Results also show that the proposed system is highly sensitive to correlation at the transmitting node. In particular, transmit-side correlation degrades link reliability by 4 orders of magnitude for the 2 × 3 8APSK configuration studied at 25 dB.

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Section: Correlated Error Performancementioning

confidence: 99%

A multiple‐input, multiple‐output broadcasting system with space, time, polarization, and labeling diversity

Patel

Quazi

2022

Trans Emerging Tel Tech

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“…In this respect, the multiple-input multiple-output (MIMO) [59] and massive MIMO [60] technology can revolutionize NTNs by exploiting spatial diversity and multiplexing as well as serving multiple ground nodes through multi-user (MU) MIMO [61]. In this direction, the extension of the DVB-Satellite to Handheld (DVB-SH) [62] and DVB-Next Generation Handheld (DVB-NGH) [63] standards to introduce MIMO configurations has been suggested with minor modifications. Besides the above, the mm-wave frequencies have been proposed as key enablers of 5G and IoT systems to attain sufficient bandwidth [60].…”

Section: State Of the Art In Wireless Communication And Networking Tementioning

confidence: 99%

AI-Inspired Non-Terrestrial Networks for IIoT: Review on Enabling Technologies and Applications

Michailidis

Potirakis

Kanatas

2020

IoT

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During the last few years, various Industrial Internet of Things (IIoT) applications have emerged with numerous network elements interconnected using wired and wireless communication technologies and equipped with strategically placed sensors and actuators. This paper justifies why non-terrestrial networks (NTNs) will bring the IIoT vision closer to reality by providing improved data acquisition and massive connectivity to sensor fields in large and remote areas. NTNs are engineered to utilize satellites, airships, and aircrafts, which can be employed to extend the radio coverage and provide remote monitoring and sensing services. Additionally, this paper describes indicative delay-tolerant massive IIoT and delay-sensitive mission-critical IIoT applications spanning a large number of vertical markets with diverse and stringent requirements. As the heterogeneous nature of NTNs and the complex and dynamic communications scenarios lead to uncertainty and a high degree of variability, conventional wireless communication technologies cannot sufficiently support ultra-reliable and low-latency communications (URLLC) and offer ubiquitous and uninterrupted interconnectivity. In this regard, this paper sheds light on the potential role of artificial intelligence (AI) techniques, including machine learning (ML) and deep learning (DL), in the provision of challenging NTN-based IIoT services and provides a thorough review of the relevant research works. By adding intelligence and facilitating the decision-making and prediction procedures, the NTNs can effectively adapt to their surrounding environment, thus enhancing the performance of various metrics with significantly lower complexity compared to typical optimization methods.

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“…Generally, the study of MIMO over SATCOM can be divided into two categories: single-user case and multi-user case. In single-user case, MIMO channel can be built by using dual polarization antennas [8]- [10], multiple earth stations [8], [11], multiple satellites [8], [12], etc. For multi-user case, plenty of user terminals (UTs) are usually served by the multibeam satellite.…”

Section: Introductionmentioning

confidence: 99%

Downlink Transmit Design for Massive MIMO LEO Satellite Communications

Li,

You,

Wang

et al. 2020

Preprint

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Low earth orbit (LEO) satellite communication systems have attracted extensive attention due to their smaller pathloss, shorter round-trip delay and lower launch cost compared with geostationary counterparts. In this paper, the downlink transmit design for massive multiple-input multiple-output (MIMO) LEO satellite communications is investigated. First, we establish the massive MIMO LEO satellite channel model where the satellite and user terminals (UTs) are both equipped with the uniform planar arrays. Then, the rank of transmit covariance matrix of each UT is shown to be no larger than one to maximize ergodic sum rate, which reveals the optimality of single-stream precoding for each UT. The minorization-maximization algorithm is used to compute the precoding vectors. To reduce the computation complexity, an upper bound of ergodic sum rate is resorted to produce a simplified transmit design, where the rank of optimal transmit covariance matrix of each UT is also shown to not exceed one. To tackle the simplified precoder design, we derive the structure of precoding vectors, and formulate a Lagrange multiplier optimization (LMO) problem building on the structure. Then, a low-complexity algorithm is devised to solve the LMO, which takes much less computation effort. Simulation results verify the performance of proposed approaches.

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MIMO for Mobile Satellite Digital Broadcasting: From Theory to Practice

Cited by 21 publications

References 22 publications

A multiple‐input, multiple‐output broadcasting system with space, time, polarization, and labeling diversity

A multiple‐input, multiple‐output broadcasting system with space, time, polarization, and labeling diversity

AI-Inspired Non-Terrestrial Networks for IIoT: Review on Enabling Technologies and Applications

Downlink Transmit Design for Massive MIMO LEO Satellite Communications

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