| 1. |
- Cheng, Hei Victor
(författare)
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Optimizing Massive MIMO : Precoder Design and Power Allocation
- 2018
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The past decades have seen a rapid growth of mobile data traffic,both in terms of connected devices and data rate. To satisfy the evergrowing data traffic demand in wireless communication systems, thecurrent cellular systems have to be redesigned to increase both spectralefficiency and energy efficiency. Massive MIMO(Multiple-Input-Multiple-Output) is one solution that satisfy bothrequirements. In massive MIMO systems, hundreds of antennas areemployed at the base station to provide service to many users at thesame time and frequency. This enables the system to serve the userswith uniformly good quality of service simultaneously, with low-costhardware and without using extra bandwidth and energy. To achievethis, proper resource allocation is needed. Among the availableresources, transmit power beamforming are the most important degrees offreedom to control the spectral efficiency and energy efficiency. Dueto the use of excessive number of antennas and low-end hardware at thebase station, new aspects of power allocation and beamforming compared to currentsystems arises.In the first part of the thesis, new uplink power allocation schemes that based on long term channel statistics isproposed. Since quality of the channel estimates is crucial in massive MIMO, in addition to data power allocation, joint power allocationthat includes the pilot power as additional variable should be considered. Therefore a new framework for power allocation thatmatches practical systems is developed, as the methods developed in the literature cannot be applied directly to massive MIMO systems. Simulation results confirm the advantages brought by the the proposed new framework.In the second part, we introduces a new approach to solve the joint precoding and power allocation for different objective in downlink scenarios by a combination of random matrix theory and optimization theory. The new approach results in a simplified problem that, though non-convex, obeys a simple separable structure. Simulation results showed that the proposed scheme provides large gains over heuristic solutions when the number of users in the cell is large, which is suitable for applying in massive MIMO systems.In the third part we investigate the effects of using low-end amplifiers at the basestations. The non-linear behavior of power consumption in these amplifiers changes the power consumption model at the basestation, thereby changes the power allocation and beamforming design. Different scenarios are investigated and resultsshow that a certain number of antennas can be turned off in some scenarios.In the last part we consider the use of non-orthogonal-multiple-access (NOMA) inside massive MIMO systems in practical scenarios where channel state information (CSI) is acquired through pilot signaling. Achievable rate analysis is carried out for different pilot signaling schemes including both uplink and downlink pilots. Numerical results show that when downlink CSI is available at the users, our proposed NOMA scheme outperforms orthogonal schemes. However with more groups of users present in the cell, it is preferable to use multi-user beamforming in stead of NOMA.
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| 2. |
- Karlsson, Marcus, 1988-
(författare)
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Blind Massive MIMO Base Stations : Downlink Transmission and Jamming
- 2018
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Massive MIMO (Multiple-Input--Multiple-Output) is a cellular-network technology in which the base station is equipped with a large number of antennas and aims to serve several different users simultaneously, on the same frequency resource through spatial multiplexing. This is made possible by employing efficient beamforming, based on channel estimates acquired from uplink reference signals, where the base station can transmit the signals in such a way that they add up constructively at the users and destructively elsewhere. The multiplexing together with the array gain from the beamforming can increase the spectral efficiency over contemporary systems.One challenge of practical importance is how to transmit data in the downlink when no channel state information is available. When a user initially joins the network, prior to transmitting uplink reference signals that enable beamforming, it needs system information---instructions on how to properly function within the network. It is transmission of system information that is the main focus of this thesis. In particular, the thesis analyzes how the reliability of the transmission of system information depends on the available amount of diversity. It is shown how downlink reference signals, space-time block codes, and power allocation can be used to improve the reliability of this transmission.In order to estimate the uplink and downlink channels from uplink reference signals, which is imperative to ensure scalability in the number of base station antennas, massive MIMO relies on channel reciprocity. This thesis shows that the principles of channel reciprocity can also be exploited by a jammer, a malicious transmitter, aiming to disrupt legitimate communication between two single-antenna devices. A heuristic scheme is proposed in which the jammer estimates the channel to a target device blindly, without any knowledge of the transmitted legitimate signals, and subsequently beamforms noise towards the target. Under the same power constraint, the proposed jammer can disrupt the legitimate link more effectively than a conventional omnidirectional jammer in many cases.
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| 3. |
- Do, Tan Tai, et al.
(författare)
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Jamming-Resistant Receivers for the Massive MIMO Uplink
- 2018
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Ingår i: IEEE Transactions on Information Forensics and Security. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 1556-6013 .- 1556-6021. ; 13:1, s. 210-223
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Tidskriftsartikel (refereegranskat)abstract
- We design a jamming-resistant receiver scheme to enhance the robustness of a massive MIMO uplink system against jamming. We assume that a jammer attacks the system both in the pilot and data transmission phases. The key feature of the proposed scheme is that, in the pilot phase, the base station estimates not only the legitimate channel, but also the jamming channel by exploiting a purposely unused pilot sequence. The jamming channel estimate is used to construct linear receiver filters that reject the impact of the jamming signal. The performance of the proposed scheme is analytically evaluated using the asymptotic properties of massive MIMO. The best regularized zero-forcing receiver and the optimal power allocations for the legitimate system and the jammer are also studied. Numerical results are provided to verify our analysis and show that the proposed scheme greatly improves the achievable rates, as compared with conventional receivers. Interestingly, the proposed scheme works particularly well under strong jamming attacks, since the improved estimate of the jamming channel outweighs the extra jamming power.
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| 4. |
- Interdonato, Giovanni, 1986-
(författare)
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Signal Processing Aspects of Cell-Free Massive MIMO
- 2018
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The fifth generation of mobile communication systems (5G) promises unprecedented levels of connectivity and quality of service (QoS) to satisfy the incessant growth in the number of mobile smart devices and the huge increase in data demand. One of the primary ways 5G network technology will be accomplished is through network densification, namely increasing the number of antennas per site and deploying smaller and smaller cells.Massive MIMO, where MIMO stands for multiple-input multiple-output, is widely expected to be a key enabler of 5G. This technology leverages an aggressive spatial multiplexing, from using a large number of transmitting/receiving antennas, to multiply the capacity of a wireless channel. A massive MIMO base station (BS) is equipped with a large number of antennas, much larger than the number of active users. The users are coherently served by all the antennas, in the same time-frequency resources but separated in the spatial domain by receiving very directive signals. By supporting such a highly spatially-focused transmission (precoding), massive MIMO provides higher spectral and energy efficiency, and reduces the inter-cell interference compared to existing mobile systems. The inter-cell interference is however becoming the major bottleneck as we densify the networks. It cannot be removed as long as we rely on a network-centric implementation, since the inter-cell interference concept is inherent to the cellular paradigm.Cell-free massive MIMO refers to a massive MIMO system where the BS antennas, herein referred to as access points (APs), are geographically spread out. The APs are connected, through a fronthaul network, to a central processing unit (CPU) which is responsible for coordinating the coherent joint transmission. Such a distributed architecture provides additional macro-diversity, and the co-processing at multiple APs entirely suppresses the inter-cell interference. Each user is surrounded by serving APs and experiences no cell boundaries. This user-centric approach, combined with the system scalability that characterizes the massive MIMO design, constitutes a paradigm shift compared to the conventional centralized and distributed wireless communication systems. On the other hand, such a distributed system requires higher capacity of back/front-haul connections, and the signal co-processing increases the signaling overhead.In this thesis, we focus on some signal processing aspects of cell-free massive MIMO. More specifically, we firstly investigate if the downlink channel estimation, via downlink pilots, brings gains to cell-free massive MIMO or the statistical channel state information (CSI) knowledge at the users is enough to reliably perform data decoding, as in conventional co-located massive MIMO. Allocating downlink pilots is costly resource-wise, thus we also propose resource saving-oriented strategies for downlink pilot assignment. Secondly, we study further fully distributed and scalable precoding schemes in order to outperform cell-free massive MIMO in its canonical form, which consists in single-antenna APs implementing conjugate beamforming (also known as maximum ratio transmission).
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| 5. |
- Sadeghi, Meysam, et al.
(författare)
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Joint Unicast and Multi-Group Multicast Transmission in Massive MIMO Systems
- 2018
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Ingår i: IEEE Transactions on Wireless Communications. - : Institute of Electrical and Electronics Engineers (IEEE). - 1536-1276 .- 1558-2248. ; 17:10, s. 6375-6388
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Tidskriftsartikel (refereegranskat)abstract
- We study the joint unicast and multi-group multicast transmission in massive multiple-input multiple-output systems. We consider a system model that accounts for channel estimation and pilot contamination and derive achievable spectral efficiencies (SEs) for unicast and multicast user terminals (UTs) under maximum ratio transmission and zero-forcing precoding. For unicast transmission, our objective is to maximize the weighted sum SE of the unicast UTs, and for the multicast transmission, our objective is to maximize the minimum SE of the multicast UTs. These two objectives are coupled in a conflicting manner, due to their shared power resource. Therefore, we formulate a multiobjective optimization problem (MOOP) for the two conflicting objectives. We derive the Pareto boundary of the MOOP analytically. As each Pareto optimal point describes a particular efficient tradeoff between the two objectives of the system, we determine the values of the system parameters (uplink training powers, downlink transmission powers, and so on) to achieve any desired Pareto optimal point. Moreover, we prove that the Pareto region is convex, and hence, the system should serve the unicast and multicast UTs at the same time-frequency resource. Finally, we validate our results using numerical simulations.
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| 6. |
- Van Chien, Trinh, 1989-, et al.
(författare)
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Joint Pilot Design and Uplink Power Allocation in Multi-Cell Massive MIMO Systems
- 2018
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Ingår i: IEEE Transactions on Wireless Communications. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 1536-1276 .- 1558-2248. ; 17:3, s. 2000-2015
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Tidskriftsartikel (refereegranskat)abstract
- This paper considers pilot design to mitigate pilot contamination and provide good service for everyone in multi-cell massive multiple-input-multiple-output systems. Instead of modeling the pilot design as a combinatorial assignment problem, as in prior works, we express the pilot signals using a pilot basis and treat the associated power coefficients as continuous optimization variables. We compute a lower bound on the uplink capacity for Rayleigh fading channels with maximum ratio detection that applies with arbitrary pilot signals. We further formulate the max-min fairness problem under power budget constraints, with the pilot signals and data powers as optimization variables. Because this optimization problem is non-deterministic polynomial-time hard due to signomial constraints, we then propose an algorithm to obtain a local optimum with polynomial complexity. Our framework serves as a benchmark for pilot design in scenarios with either ideal or non-ideal hardware. Numerical results manifest that the proposed optimization algorithms are close to the optimal solution obtained by exhaustive search for different pilot assignments and the new pilot structure and optimization bring large gains over the state-of-the-art suboptimal pilot design.
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