1. |
- Suraweera, Himal, et al.
(author)
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Multi-pair amplify-and-forward relaying with very large antenna arrays
- 2013
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In: Proceedings of the IEEE International Conference on Communicatons (ICC). - Budapest : IEEE. - 9781467331227 ; , s. 4635-4640
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Conference paper (peer-reviewed)abstract
- We consider a multi-pair relay channel where multiple sources simultaneously communicate with destinations using a relay. Each source or destination has only a single antenna, while the relay is equipped with a very large antenna array. We investigate the power efficiency of this system when maximum ratio combining/maximal ratio transmission (MRC/MRT) or zero-forcing (ZF) processing is used at the relay. Using a very large array, the transmit power of each source or relay (or both) can be made inversely proportional to the number of relay antennas while maintaining a given quality-of-service. At the same time, the achievable sum rate can be increased by a factor of the number of source-destination pairs. We show that when the number of antennas grows to infinity, the asymptotic achievable rates of MRC/MRT and ZF are the same if we scale the power at the sources. Depending on the large scale fading effect, MRC/MRT can outperform ZF or vice versa if we scale the power at the relay.
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2. |
- Vu, Thanh Tung, et al.
(author)
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Energy-Efficient Massive MIMO for Federated Learning : Transmission Designs and Resource Allocations
- 2022
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In: IEEE Open Journal of the Communications Society. - : Institute of Electrical and Electronics Engineers (IEEE). - 2644-125X. ; 3, s. 2329-2346
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Journal article (peer-reviewed)abstract
- This work proposes novel synchronous, asynchronous, and session-based designs for energy-efficient massive multiple-input multiple-output networks to support federated learning (FL). The synchronous design relies on strict synchronization among users when executing each FL communication round, while the asynchronous design allows more flexibility for users to save energy by using lower computing frequencies. The session-based design splits the downlink and uplink phases in each FL communication round into separate sessions. In this design, we assign users such that one of the participating users in each session finishes its transmission and does not join the next session. As such, more power and degrees of freedom will be allocated to unfinished users, resulting in higher rates, lower transmission times, and hence, higher energy efficiency. In all three designs, we use zero-forcing processing for both uplink and downlink, and develop algorithms that optimize user assignment, time allocation, power, and computing frequencies to minimize the energy consumption at the base station and users, while guaranteeing a predefined maximum execution time of each FL communication round.
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3. |
- Vu, Tung T., et al.
(author)
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Energy-Efficient Massive MIMO for Serving Multiple Federated Learning Groups
- 2021
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In: 2021 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM). - : IEEE. - 9781728181042
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Conference paper (peer-reviewed)abstract
- With its privacy preservation and communication efficiency, federated learning (FL) has emerged as a learning framework that suits beyond SG and towards 6G systems. This work looks into a future scenario in which there are multiple groups with different learning purposes and participating in different FL processes. We give energy-efficient solutions to demonstrate that this scenario can be realistic. First, to ensure a stable operation of multiple FL processes over wireless channels, we propose to use a massive multiple-input multiple-output network to support the local and global FL training updates, and let the iterations of these FL processes be executed within the same large-scale coherence time. Then, we develop asynchronous and synchronous transmission protocols where these iterations are asynchronously and synchronously executed, respectively, using the downlink unicasting and conventional uplink transmission schemes. Zero-forcing processing is utilized for both uplink and downlink transmissions. Finally, we propose an algorithm that optimally allocates power and computation resources to save energy at both base station and user sides, while guaranteeing a given maximum execution time threshold of each FL iteration. Compared to the baseline schemes, the proposed algorithm significantly reduces the energy consumption, especially when the number of base station antennas is large.
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4. |
- Al-Hraishawi, Hayder, et al.
(author)
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Multi-Cell Massive MIMO Uplink With Underlay Spectrum Sharing
- 2019
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In: IEEE Transactions on Cognitive Communications and Networking. - : IEEE. - 2332-7731. ; 5:1, s. 119-137
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Journal article (peer-reviewed)abstract
- The achievable rates are investigated for multicell multi-user massive multiple-input multiple-output (MIMO) systems with underlay spectrum sharing. A general pilot sharing scheme and two pilot sequence designs (PSDs) are investigated via fully shared (PSD-1) and partially shared (PSD-2) uplink pilots. The number of simultaneously served primary users and secondary users (SUs) in the same time-frequency resource block by the PSD-1 is higher than that of PSD-2. The transmit power constraints for the SUs are derived to mitigate the secondary co-channel interference (CCI) inflicted at the primary base-station (PBS) subject to a predefined primary interference temperature (PIT). The optimal transmit power control coefficients for the SUs with max-min fairness and the common achievable rates are derived. The cumulative detrimental effects of channel estimation errors, CCI and intra-cell/inter-cell pilot contamination are investigated. The secondary transmit power constraint and the achievable rates for the perfect channel state information (CSI) case become independent of the PIT when the number of PBS antennas grows unbounded. Therefore, the primary and secondary systems can be operated independent of each other as both intra-cell and inter-cell interference can be asymptotically mitigated at the massive MIMO PBS and secondary base-station. Nevertheless, the achievable rates and secondary power constraints for the imperfect CSI case with PSD-1 are severely degraded due to the presence of intra-cell and inter-cell pilot contamination. These performance metrics depend on the PIT even in the asymptotic PBS antenna regime. Hence, the primary and secondary systems can no longer be operated independently for imperfect CSI with PSD-1. However, PSD-2 provides an achievable rate gain over PSD-1 despite the requirement of lengthier pilot sequences of the former than that of the latter.
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5. |
- Bashar, Manijeh, et al.
(author)
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Energy Efficiency of the Cell-Free Massive MIMO Uplink with Optimal Uniform Quantization
- 2019
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In: IEEE Transactions on Green Communications and Networking. - : IEEE. - 2473-2400. ; 3:4, s. 971-987
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Journal article (peer-reviewed)abstract
- A cell-free Massive multiple-input multiple-output (MIMO) uplink is considered, where the access points (APs) are connected to a central processing unit (CPU) through limited-capacity wireless microwave links. The quantized version of the weighted signals are available at the CPU, by exploiting the Bussgang decomposition to model the effect of quantization. A closed-form expression for spectral efficiency is derived taking into account the effects of channel estimation error and quantization distortion. The energy efficiency maximization problem is considered with per-user power, backhaul capacity and throughput requirement constraints. To solve this non-convex problem, we decouple the original problem into two sub-problems, namely, receiver filter coefficient design, and power allocation. The receiver filter coefficient design is formulated as a generalized eigenvalue problem whereas a successive convex approximation (SCA) and a heuristic sub-optimal scheme are exploited to convert the power allocation problem into a standard geometric programming (GP) problem. An iterative algorithm is proposed to alternately solve each sub-problem. Complexity analysis and convergence of the proposed schemes are investigated. Numerical results indicate the superiority of the proposed algorithms over the case of equal power allocation.
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6. |
- Bashar, Manijeh, et al.
(author)
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On the Energy Efficiency of Limited-Backhaul Cell-Free Massive MIMO
- 2019
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In: ICC 2019 - 2019 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC). - : IEEE. - 9781538680889 - 9781538680896
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Conference paper (peer-reviewed)abstract
- We investigate the energy efficiency performance of cell-free Massive multiple-input multiple-output (MIMO), where the access points (APs) are connected to a central processing unit (CPU) via limited-capacity links. Thanks to the distributed maximum ratio combining (MRC) weighting at the APs, we propose that only the quantized version of the weighted signals are sent back to the CPU. Considering the effects of channel estimation errors and using the Bussgang theorem to model the quantization errors, an energy efficiency maximization problem is formulated with per-user power and backhaul capacity constraints as well as with throughput requirement constraints. To handle this non-convex optimization problem, we decompose the original problem into two sub-problems and exploit a successive convex approximation (SCA) to solve original energy efficiency maximization problem. Numerical results confirm the superiority of the proposed optimization scheme.
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7. |
- Bashar, Manijeh, et al.
(author)
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On the Performance of Backhaul Constrained Cell-Free Massive MIMO with Linear Receivers
- 2018
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In: 2018 CONFERENCE RECORD OF 52ND ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS, AND COMPUTERS. - : IEEE. - 9781538692189 ; , s. 624-628
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Conference paper (peer-reviewed)abstract
- Limited-backhaul cell-free Massive multiple-input multiple-output (MIMO), in which the fog radio access network (F-RAN) is implemented to exchange the information between access points (APs) and the central processing unit (CPU), is investigated. We introduce a novel approach where the APs estimate the channel and send back the quantized version of the estimated channel and the quantized version of the received signal to the central processing unit. The Max algorithm and the Bussgang theorem are exploited to model the optimum uniform quantization. The ergodic achievable rates are derived. We show that exploiting microwave wireless backhaul links and using a small number of hits to quantize the estimated channel and the received signal, the performance of limited-backhaul cell-free Massive MIMO closely approaches the performance of cell-free Massive MIMO with perfect backhaul links.
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8. |
- Bashar, Manijeh, et al.
(author)
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Uplink Spectral and Energy Efficiency of Cell-Free Massive MIMO With Optimal Uniform Quantization
- 2021
-
In: IEEE Transactions on Communications. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 0090-6778 .- 1558-0857. ; 69:1, s. 223-245
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Journal article (peer-reviewed)abstract
- This paper investigates the performance of limited-fronthaul cell-free massive multiple-input multiple-output (MIMO) taking account the fronthaul quantization and imperfect channel acquisition. Three cases are studied, which we refer to as Estimate&Quantize, Quantize&Estimate, and Decentralized, according to where channel estimation is performed and exploited. Maximum-ratio combining (MRC), zero-forcing (ZF), and minimum mean-square error (MMSE) receivers are considered. The Max algorithm and the Bussgang decomposition are exploited to model optimum uniform quantization. Exploiting the optimal step size of the quantizer, analytical expressions for spectral and energy efficiencies are presented. Finally, an access point (AP) assignment algorithm is proposed to improve the performance of the decentralized scheme. Numerical results investigate the performance gap between limited fronthaul and perfect fronthaul cases, and demonstrate that exploiting relatively few quantization bits, the performance of limited-fronthaul cell-free massive MIMO closely approaches the perfect-fronthaul performance.
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9. |
- Chien, Trinh Van, et al.
(author)
-
Uplink Power Control in Cellular Massive MIMO Systems : Coping With the Congestion Issue
- 2020
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In: 2020 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS WORKSHOPS (ICC WORKSHOPS). - : IEEE.
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Conference paper (peer-reviewed)abstract
- One main goal of 5G-and-beyond systems is to simultaneously serve many users, each having a requested spectral efficiency (SE), in an energy-efficient way. The network capacity cannot always satisfy all the SE requirements, for example, when some users have bad channel conditions, especially happening in a cellular topology, and therefore congestion can happen. By considering both the pilot and data powers in the uplink transmission as optimization variables, this paper formulates and solves an energy-efficiency problem for cellular Massive MIMO (Multiple Input Multiple Output) systems that can handle the congestion issue. New algorithms based on the alternating optimization approach are proposed to obtain a fixed-point solution. Numerical results manifest that the proposed algorithms can provide the demanded SEs to many users even when the congestion happens.
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10. |
- Duc Ho, Chung, et al.
(author)
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Multi-way Massive MIMO Relay Networks with Maximum-Ratio Processing
- 2017
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In: 2017 INTERNATIONAL CONFERENCE ON RECENT ADVANCES IN SIGNAL PROCESSING, TELECOMMUNICATIONS and COMPUTING (SIGTELCOM). - : IEEE. - 9781509022915 - 9781509022922 ; , s. 124-128
-
Conference paper (peer-reviewed)abstract
- This paper considers a multi-way massive multiple-input multiple-output (MIMO) relaying system. The bearing-information is exchanged among multiple users with the help of a multiple-antenna relay (the base station). The maximum-ratio (MR) processing is applied at the relay under the assumption of perfect channel state information. The spectral efficiency and the asymptotic results for the signal-to-interference-plus-noise ratio (when the number of relay antennas becomes large) are derived. By using a massive number of antennas, the transmit power at both user side and/or relay can be made inversely proportional to the number of relay antennas without degradation in the system performance.
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