SWIPT in Hybrid Relay-Assisted Massive MIMO Downlink

Shrestha, Rajan; Amarasuriya, Gayan

doi:10.1109/icc.2019.8761553

Cited by 4 publications

(11 citation statements)

References 12 publications

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“…In [30], efficient user association techniques for wireless energy transfer in massive MIMO heterogeneous networks are proposed. In [31], [32], the feasibility of adopting dual-hop massive MIMO relay networks in boosting the performance of SWIPT is investigated. In [9], the performance metrics of SWIPT in multi-cell massive MIMO multi-way relay networks are derived in the presence of erroneously estimated CSI.…”

Section: A Swipt With Co-located Massive Mimomentioning

confidence: 99%

“…Even though there exists a handful of research on SWIPT in co-located massive MIMO [9], [26]- [32], the fundamental performance metrics have not yet been established in the context of SWIPT-enabled cell-free massive MIMO. It has been already shown that the data rate performance of cell-free massive MIMO is fundamentally different from that of the co-located counterpart [20].…”

Section: Difference Relative To the Existing Literaturementioning

confidence: 99%

“…It has been already shown that the data rate performance of cell-free massive MIMO is fundamentally different from that of the co-located counterpart [20]. Thus, the performance bounds of SWIPT in cell-free massive MIMO are also expected to be considerably different from those established for co-located counterpart [9], [27]- [32]. This is because not only users but also APs are geographically distributed, and hence, the harvested energy and rates are severely hindered by the nearfar effects.…”

Section: Difference Relative To the Existing Literaturementioning

confidence: 99%

“…All related prior works on SWIPT-enabled massive MIMO [9], [26]- [32] utilize linear energy harvesting models at the users. Nonetheless, our analysis deviates from this ideal model by adopting a practically viable SWIPT model proposed by [14], which can capture non-linear characteristics of energy harvesting circuitry.…”

Section: Difference Relative To the Existing Literaturementioning

confidence: 99%

“…Moreover, by adopting a hybrid TS/PS protocol from [35], we generalize our performance analysis for both TS and PS protocols. Although the impact of imperfectly estimated UL channels has been investigated to design precoders for SWIPT-enabled massive MIMO [31], [32], the users have been assumed to rely on statistical CSI. This assumption can be justified for co-located massive MIMO because the instantaneous channel coefficients can be approximated tightly by their average counterparts when the number of co-located antennas grows without bound [34].…”

Section: Difference Relative To the Existing Literaturementioning

confidence: 99%

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Exploiting Cell-Free Massive MIMO for Enabling Simultaneous Wireless Information and Power Transfer

Galappaththige¹,

Shrestha²,

Baduge³

2020

Preprint

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The performance of simultaneous wireless information and power transfer (SWIPT) in downlink (DL) cell-free massive multiple-input multiple-output (MIMO) is investigated. Tight approximations to the DL harvested energy and the DL/uplink (UL) achievable rates are derived for two practical channel state information (CSI) cases by using a non-linear energy harvesting model for time-switching and power-splitting protocols. Max-min fairness-based transmit power control policies are employed to mitigate the deleterious near-far effects caused by distributed transmissions/receptions in cell-free massive MIMO. The achievable common DL energy-rate trade-off is derived, and thereby, it is shown that the proposed maxmin power control guarantees user-fairness regardless of nearfar effects in terms of both harvested energy and achievable rate. The benefits of user estimated DL CSI to boost the SWIPT performance are explored. These performance metrics are compared against those of the conventional co-located massive MIMO, and thereby, it is revealed that the reduction of path-losses and lower average transmit powers offered by cell-free massive MIMO can be exploited to boost the energyrate trade-off of SWIPT at the expense of increased backhaul requirements.

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Section: A Swipt With Co-located Massive Mimomentioning

confidence: 99%

Section: Difference Relative To the Existing Literaturementioning

confidence: 99%

Section: Difference Relative To the Existing Literaturementioning

confidence: 99%

Section: Difference Relative To the Existing Literaturementioning

confidence: 99%

Section: Difference Relative To the Existing Literaturementioning

confidence: 99%

See 3 more Smart Citations

Exploiting Cell-Free Massive MIMO for Enabling Simultaneous Wireless Information and Power Transfer

Galappaththige¹,

Shrestha²,

Baduge³

2020

Preprint

Self Cite

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Modified User Grouping and Hybrid Precoding for Information Decoding and Energy Harvesting in Hardware Impaired Point-To-Point MM-Wave Massive MIMO NOMA

Audu

Oyerinde

2023

IEEE Access

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The fifth generation (5G) and beyond 5G race covers both spectral-efficient and energy-efficient mechanisms such as simultaneous wireless information decoding and energy harvesting (SWIDEH). Structured as full or sub-connection of hybrid-precoded mm-wave massive multiple-input multiple-output non-orthogonal multiple access (NOMA) systems. However, the more practical hardwareimpaired (HI) functionality yet to be considered for point-to-point (p-to-p) MIMO is conceived from an existing system. A hardware impairment-based power splitting is proposed for energy harvesting. The energy of the HI signal is harnessed through the joint optimization of power allocation (PA) for information decoding (ID) and the power splitting (PS) factor for energy harvesting (EH) using zero-forcing (ZF) precoding and minimum mean square error (MMSE) downlink (DL) detection. Based on the simulation results, an adaptive cluster head selection (CHS) criterion is proposed for analog precoding to mitigate intracluster interferences at a high signal-to-noise ratio (SINR). A successive interference cancellation (SIC) is carried out to enable dynamic channel overhead estimation and user signal detection. An investigation is done by simulating the system performance at varied numbers of users, the number of radio-frequency (RF) chains, and channel characteristics for modelling the user group threshold coupled with channel size reduction via an antenna selection scheme. Observing the execution time and some graphical plots shows that the spectral and energy efficiency can be improved by a random (R) or maximum norm average (MNA) channel vector formation from each user's channel matrix combined with the best adaptive correlation threshold during CHS and a regularized ZF (RZF) precoder.INDEX TERMS adaptive correlation threshold, hardware-impaired (HI), hybrid-precoding, massive multiple-input multiple-output (mMIMO), mm-wave (mmWave), non-orthogonal multiple access (NOMA), point-to-point (p-to-p) MIMO, simultaneous wireless information decoding and energy harvesting (SWIDEH).

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Magnetic Coupling Resonant Simultaneous Wireless Power and Information Transfer System with Switched Relay Resonators

Han

Wang

Zhang

et al. 2021

2021 IEEE Asia-Pacific Microwave Conference (APMC)

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SWIPT in Hybrid Relay-Assisted Massive MIMO Downlink

Cited by 4 publications

References 12 publications

Exploiting Cell-Free Massive MIMO for Enabling Simultaneous Wireless Information and Power Transfer

Exploiting Cell-Free Massive MIMO for Enabling Simultaneous Wireless Information and Power Transfer

Modified User Grouping and Hybrid Precoding for Information Decoding and Energy Harvesting in Hardware Impaired Point-To-Point MM-Wave Massive MIMO NOMA

Magnetic Coupling Resonant Simultaneous Wireless Power and Information Transfer System with Switched Relay Resonators

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