Large System Analysis of Sum Capacity in the Gaussian MIMO Broadcast Channel

Guthy, Christian; Utschick, Wolfgang; Honig, Michael L.

doi:10.1109/jsac.2013.130204

Cited by 29 publications

(13 citation statements)

References 23 publications

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“…This GIA is extended to a multi-cell interfering MIMO-BC in [109], where both the feasible condition on the GIA and a low complexity IA decoder design are studied. For the performance analysis of massive MIMO system, there exists a large set of tools from random matrix theory (see [110][111][112][113][114][115][116] and references therein).…”

Section: Massive and Full-dimension Mimo Technologiesmentioning

confidence: 99%

Enabling 5G mobile wireless technologies

Lau

Jorswieck

et al. 2015

J Wireless Com Network

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Research on 5G mobile wireless technologies has been very active in both academia and industry in the past few years. While there has been certain consensus on the overall requirements of 5G wireless systems (e.g., in data rate, network capacity, delay), various enabling wireless technologies have been considered and studied to achieve these performance targets. It has been quite clear, however, that there would be no single enabling technology that can achieve all diverse and even conflicting 5G requirements. In general, many fundamental changes and innovations to re-engineer the overall network architecture and algorithms in different layers and to exploit new system degrees of freedom would be needed for the future 5G wireless system. In particular, we may need to consider other potential waveform candidates that can overcome limitations of the orthogonal frequency multiple access (OFDM) waveform employed in the current 4G system, develop disruptive technologies to fulfill 5G rate and capacity requirements including network densification, employment of large-scale (massive) multiple input multiple output (MIMO), and exploitation of the millimeter wave (mmWave) spectrum to attain Gigabit communications. In addition, design tools from the computer networking domain including software defined networking, virtualization, and cloud computing are expected to play important roles in defining the more flexible, intelligent, and efficient 5G network architecture. This paper aims at describing key 5G enabling wireless mobile technologies and discussing their potentials and open research challenges. We also present how papers published in our special issue contribute to the developments of these disruptive 5G technologies.

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Section: Massive and Full-dimension Mimo Technologiesmentioning

confidence: 99%

Enabling 5G mobile wireless technologies

Lau

Jorswieck

et al. 2015

J Wireless Com Network

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“…The LISA method is a linear version of the earlier proposed Successive Encoding and Successive Allocation Method (SESAM) [23], [24], that combines the successive allocation of data streams to MSs with a successive encoding technique based on the coding technique with known interference introduced in [25]. Its excellent properties have been demonstrated in measurement campaigns [26], [27] and later confirmed by means of large system analysis results in [28], [29]. LISA successively allocates data streams to the MSs, and determines the precoders and equalizers for those data streams, which circumvents the high computational complexity of the direct sum rate maximization while maintaining the performance of state-of-the-art methods for achieving high sum rates in multiuser MIMO systems.…”

Section: Introductionmentioning

confidence: 99%

Hybrid LISA Precoding for Multiuser Millimeter-Wave Communications

Utschick

Stockle

Joham

et al. 2018

IEEE Trans. Wireless Commun.

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Millimeter-wave (mmWave) communications plays an important role for future cellular networks because of the vast amount of spectrum available in the underutilized mmWave frequency bands. To overcome the huge free space omnidirectional path loss in those frequency bands, the deployment of a very large number of antenna elements at the base station is crucial. The complexity, power consumption and costs resulting from the large number of antenna elements can be reduced by limiting the number of RF chains. This leads to hybrid precoding and combining, which, in contrast to the traditional fully digital precoding and combining, moves a part of the signal processing from the digital to the analog domain. This paper proposes new algorithms for the design of hybrid precoders and combiners in a multiuser scenario. The algorithms are based on the previously proposed Linear Successive Allocation method developed for the traditional fully digital version. It successively allocates data streams to users and suppresses the respective interstream interference in two stages, which perfectly matches the hybrid architecture. Furthermore, a low-complexity version is developed by exploiting the typical structure of mmWave channels. The good performance of the proposed method and its low-complexity version is demonstrated by simulation results. Index TermsMultiuser communications, mmWave communications, hybrid precoding, linear successive allocation method, structured mmWave channels.The authors are with Methods of Signal Processing,

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“…Compared to the number of antennas in 4G, which is utmost four for the long term evolution (LTE) and up to eight for LTE Advanced (LTE-A), the number of antennas of M-MIMO system increases by one or two orders of magnitude [21,23]. The users located within the coverage area of the BS use the degrees of freedom provided by large scale antennas array to communicate with BS simultaneously within the same time-frequency resource, which not only significantly increases the throughput [3,12,15,6], and by orders of magnitude improves the spectrum efficiency, but also reduces the interference and enhances the robustness of the system [10,11,7,19,18]. Meanwhile, diversity gain and array gain it provides enable us to reduce the transmitted power and improve power efficiency significantly [2,14].…”

Section: Introductionmentioning

confidence: 99%

A New Joint Zero-Forcing Beamforming Algorithm for Massive MIMO System

Zhou¹,

Shen²,

Wang³

et al. 2017

STUD INFORM CONTROL

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Abstract:In massive multiple input multiple output (M-MIMO) systems where the number of antennas mounted at the base station (BS) is much larger than that of the mobile users, the existing beamforming schemes generally choose all users over the downlink as receivers. However, due to the fact that various channels may be significantly different, the existing solutions may not be appropriate in case that the number of users becomes sufficiently large, and hence the system throughput is not optimal. In addition, if all antennas at the BS are selected to transmit data streams, the hardware complexity requirement is consequently high, which results in the waste of RF chains and transmit power. In this paper, we propose a new zero-forcing beamforming algorithm on the basis of joint user grouping and antenna selection for M-MIMO systems. When a M-MIMO BS serves a number of users, we divide users into two groups and select an optimal antennas subset. The proposed user grouping method can maximize the total throughput by grouping users into two subsets and selecting the group with better channel station to receive data streams, and the antenna selection method aims to alleviate the system complexity and RF chains cost. The zero-forcing beamforming algorithm based on user grouping and antenna selection will greatly reduce the hardware complexity by lowering the cost and power consumption of radio-frequency chains with only a small performance loss. Simulations illustrate the proposed algorithm provides a better trade-off between the system throughput performance and the hardware complexity in M-MIMO systems.

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Large System Analysis of Sum Capacity in the Gaussian MIMO Broadcast Channel

Cited by 29 publications

References 23 publications

Enabling 5G mobile wireless technologies

Enabling 5G mobile wireless technologies

Hybrid LISA Precoding for Multiuser Millimeter-Wave Communications

A New Joint Zero-Forcing Beamforming Algorithm for Massive MIMO System

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