Bandwidth Efficiency Maximization for Single-Cell Massive Spatial Modulation MIMO: An Adaptive Power Allocation Perspective

He, Longzhuang; Wang, Jintao; Song, Jian; Hanzo, Lajos

doi:10.1109/access.2017.2668420

Cited by 9 publications

(12 citation statements)

References 25 publications

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“…The existing state-of-the-art of massive SM-MIMO systems is mainly focused on UL communications [11]- [25], where each user invokes SM to convey information and the BS employs multi-user detection to recover the transmit messages. Specifically, in [11]- [16], the advantages of massive SM-MIMO systems have been demonstrated in terms of their spectral-, energy-and cost-efficiencies. Message passing (MP) algorithms based multiuser detectors have been conceived [17]- [20] for massive SM-MIMO systems communicating both over narrowband and broadband channels.…”

Section: A Backgroundmentioning

confidence: 99%

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A Compressive Sensing Assisted Massive SM-VBLAST System: Error Probability and Capacity Analysis

Xiao

Liu

et al. 2020

IEEE Trans. Wireless Commun.

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The concept of massive spatial modulation (SM) assisted vertical bell labs space-time (V-BLAST) (SM-VBLAST) system [1] is proposed, where SM symbols (instead of conventional constellation symbols) are mapped onto the VBLAST structure. We show that the proposed SM-VBLAST is a promising massive multiple input multiple output (MIMO) candidate owing to its high throughput and low number of radio frequency (RF) chains used at the transmitter. For the generalized massive SM-VBLAST systems, we first derive both the upper bounds of the average bit error probability (ABEP) and the lower bounds of the ergodic capacity. Then, we develop an efficient error correction mechanism (ECM) assisted compressive sensing (CS) detector whose performance tends to achieve that of the maximum likelihood (ML) detector. Our simulations indicate that the proposed ECM-CS detector is suitable both for massive SM-MIMO based point-topoint and for uplink communications at the cost of a slightly higher complexity than that of the compressive sampling matching pursuit (CoSaMP) based detector in the high SNR region.

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Section: A Backgroundmentioning

confidence: 99%

“…As a result, the values of N p l l and D p l l become important for calculating (16), which are associated with specific antenna configurations. Considering BPSK and QPSK for example, we have l can be obtained by (18).…”

Section: A Generalized Abep Analysismentioning

confidence: 99%

A Compressive Sensing Assisted Massive SM-VBLAST System: Error Probability and Capacity Analysis

Xiao

Liu

et al. 2020

IEEE Trans. Wireless Commun.

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“…This is leading to a new approach and proposal for single radio-frequency (RF) large scale MIMO system called spatial modulation massive MIMO (SM-MIMO). This is coming as a result of massive MIMO full deployment in 5G network and operators concern about the increasing capital and operational expenses as a result of its large number of RF-chain and power amplifiers leading to high energy consumption [35], [36]. Massive SM-MIMO is a novel MIMO concept that uses a large number of antenna elements than the number of RF-chains, the distinguishing feature of SM-MIMO from conventional MIMO is that it map extra information bits into what is called the ''SM constellation diagram'' in which case each constellation part is made up of either one or a subset of antenna elements [37].…”

Section: Iv5 Spatial Modulationmentioning

confidence: 99%

5G Wireless Communication Network Architecture and Its Key Enabling Technologies

Idowu-Bismark

Okokpujie

Husbands

et al. 2019

IREASE

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The wireless mobile communication systems have developed from the second generation (2G) through to the current fourth generation (4G) wireless system, transforming from simply telephony system to a network transporting rich multimedia contents including video conferencing, 3-D gaming and in-flight broadband connectivity (IFBC) where airline crew use augmented reality headsets to address passengers personally. However, there are still many challenges that are beyond the capabilities of the 4G as the demand for higher data rate, lower latency, and mobility requirement by new wireless applications sores leading to mixed contentcentric communication service. The fifth generation (5G) wireless system has thus been suggested, and research is ongoing for its deployment beyond 2020. In this article, we investigate the various challenges of 4G and propose an indoor, outdoor segregated cellular architecture with cloudbased Radio Access Network (C-RAN) for 5G, we review some of its key emerging wireless technologies needed in meeting the new demands of users including massive multiple input multiple output (mMIMO) system, Device-to-Device (D2D), Visible Light Communication (VLC), Ultra-dense network, Spatial Modulation and Millimeter wave technology. It is also shown how the benefits of the emerging technologies can be optimized using the Software Defined Networks/Network Functions Virtualization (SDN/NFV) as a tool in C-RAN. We conclude that the new 5G wireless architecture will derive its strength from leveraging on the benefits of the emerging hardware technologies been managed by reconfigurable SDN/NFV via the C-RAN. This work will be of immense help to those who will engage in further research expedition and network operators in the search for a smooth evolution of the current state of the art networks toward 5G networks.

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“…Given the subject's relative maturits by 2014, a detailed introduction of various SM-MIMO systems was given in [14]. Furthermore, authors in [15] and [16] applied the SM to a single-cell massive MIMO system with the large-scale antenna benefits taken into consideration. In addition to single-cell or pointto-point MIMOs, He et al [16] further studied the achievable uplink (UL) spectral efficiency (SE) of a multi-cell massive SM-MIMO system and derived asympototic SE lower bounds relying on linear combining schemes [17].…”

mentioning

confidence: 99%

“…Furthermore, authors in [15] and [16] applied the SM to a single-cell massive MIMO system with the large-scale antenna benefits taken into consideration. In addition to single-cell or pointto-point MIMOs, He et al [16] further studied the achievable uplink (UL) spectral efficiency (SE) of a multi-cell massive SM-MIMO system and derived asympototic SE lower bounds relying on linear combining schemes [17]. Performance of massive SM-MIMO in high-speed railway was discussed in [18] and massive SM-MIMO with forward error correction (FEC) was investigated in [19].…”

mentioning

confidence: 99%

Achievable Rate Analysis of the Generalized Spatial Modulation Uplink in Multi-Cell Multi-User Systems in the Face of Pilot Contamination

Zhang

et al. 2019

IEEE Trans. Veh. Technol.

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The sum-rate of the multi-cell multi-user generalized spatial modulation (GSM) uplink is analyzed in the presence of realistic pilot contamination. A practical channel model associated with arbitrary transmit and receive correlation matrices is assumed for each user and base station (BS). Imperfect channel estimation is assumed with pilot contamination. The performance of a single-cell based minimum mean squared error (SMMSE) combiner is analyzed and compared to the ubiquitous zero forcing (ZF) combiner as well as matched filtering (MF). The transmit antenna (TA) index detection and the classic amplitude/phase modulation (APM) signal detection process are carried out separately for the sake of low complexity. Moreover, an algorithm based on order statistics is proposed for calculating the antenna detection probability conditioned on the actual TA. Finally, an approximation of the sum-rate is derived by exploiting the characteristics of massive MIMOs. Simulation results show that SMMSE has the best performance, followed by ZF and MF. Furthermore, the relationships between the system's achievable rate and three systems parameters, namely the number of BS antennas, the signal-to-noise-ratio (SNR) and the interference factor of pilot contamination, are presented. The performance of different number of activated antennas are also compared.

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Bandwidth Efficiency Maximization for Single-Cell Massive Spatial Modulation MIMO: An Adaptive Power Allocation Perspective

Cited by 9 publications

References 25 publications

A Compressive Sensing Assisted Massive SM-VBLAST System: Error Probability and Capacity Analysis

A Compressive Sensing Assisted Massive SM-VBLAST System: Error Probability and Capacity Analysis

5G Wireless Communication Network Architecture and Its Key Enabling Technologies

Achievable Rate Analysis of the Generalized Spatial Modulation Uplink in Multi-Cell Multi-User Systems in the Face of Pilot Contamination

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