Performance Analysis of Fluid Antenna Communication Systems For Future Mobile Networks

With 6G communications comes a significant increase in standards and performance metrics when compared to 5G communications, with some 5G targets being increased by a factor of 10. Requirements such as high data rates of 1 terabit per second or higher energy efficiency are not achievable with current technologies used in 5G like massive multiple input multiple-output (MIMO). Therefore, new technologies should be incorporated in order to achieve these performance targets. Fluid an tenna communication systems (FACS) are a new technology that uses a software-controlled antenna called a fluid antenna that is able to repo sition itself in space to one of many predetermined locations, known as ports. This thesis aims to expand on existing work done in FACS and indicate its viability in the future of communication systems by estab lishing a more accurate model as well as looking at its integration with existing or emerging technologies like reflective intelligent surfaces (RIS) or modulation techniques like spatial modulation (SM). Initially, this thesis aims to establish a more accurate FACS model with the consideration of noise in a multi-user communication system where the mobile devices each have a single fluid antenna. Due to the complexity of analysis with the incorporation of noise, new approxima tions like the Gauss-Laguerre quadrature are used in order to obtain a closed-form solution. Then this thesis aims to augment FACS with ex isting technologies, with the introduction of a novel form of index modu lation called position index modulation which aims to increase the num ber of bits transmitted per symbol by assigning an index to different port groups. Finally, this thesis looks at integrating FACS with another emerging technology, RIS. RIS can augment the performance of FACS by influencing the nature of multipaths in the channel in a way that maximises the effectiveness of FAC

Joint Port Selection and Beamforming Design for Fluid Antenna Assisted Integrated Data and Energy Transfer

Integrated data and energy transfer (IDET) has been of fundamental importance for providing both wireless data transfer (WDT) and wireless energy transfer (WET) services towards low-power devices. Fluid antenna (FA) is capable of exploiting the huge spatial diversity of the wireless channel to enhance the receive signal strength, which is more suitable for the tiny-size low-power devices having the IDET requirements. In this letter, a multiuser FA assisted IDET system is studied and the weighted energy harvesting power at energy receivers (ERs) is maximized by jointly optimizing the port selection and transmit beamforming design under imperfect channel state information (CSI), while the signal-to-interference-plus-noise ratio (SINR) constraint for each data receiver (DR) is satisfied. An efficient algorithm is proposed to obtain the suboptimal solutions for the non-convex problem. Simulation results evaluate the performance of the FA-IDET system, while also demonstrate that FA outperforms the multi-input-multi-output (MIMO) counterpart in terms of the IDET performance, as long as the port number is large enough

Price-Discrimination Game for Distributed Resource Management in Federated Learning

In vanilla federated learning (FL) such as FedAvg, the parameter server (PS) and multiple distributed clients can form a typical buyer's market, where the number of PS/buyers of FL services is far less than the number of clients/sellers. In order to improve the performance of FL and reduce the cost of motivating clients to participate in FL, this paper proposes to differentiate the pricing for services provided by different clients rather than simply providing the same service pricing for different clients. The price is differentiated based on the performance improvements brought to FL and their heterogeneity in computing and communication capabilities. To this end, a price-discrimination game (PDG) is formulated to comprehensively address the distributed resource management problems in FL, including multi-objective trade-off, client selection, and incentive mechanism. As the PDG is a mixed-integer nonlinear programming (MINLP) problem, a distributed semi-heuristic algorithm with low computational complexity and low communication overhead is designed to solve it. The simulation result verifies the effectiveness of the proposed approach

Performance Analysis of Integrated Data and Energy Transfer Assisted by Fluid Antenna Systems

Fluid antenna multiple access (FAMA) is capable of exploiting the high spatial diversity of wireless channels to mitigate multi-user interference via flexible port switching, which achieves a better performance than traditional multi-input-multi-output (MIMO) systems. Moreover, integrated data and energy transfer (IDET) is able to provide both the wireless data transfer (WDT) and wireless energy transfer (WET) services towards low-power devices. In this paper, a FAMA assisted IDET system is studied, where $N$ access points (APs) provide dedicated IDET services towards $N$ user equipments (UEs). Each UE is equipped with a single fluid antenna. The performance of WDT and WET , i.e., the WDT outage probability, the WET outage probability, the reliable throughput and the average energy harvesting amount, are analysed theoretically by using time switching (TS) between WDT and WET. Numerical results validate our theoretical analysis, which reveals that the number of UEs and TS ratio should be optimized to achieve a trade-off between the WDT and WET performance. Moreover, FAMA assisted IDET achieves a better performance in terms of both WDT and WET than traditional MIMO with the same antenna size.Comment: Accepted by IEEE ICC 202

Performance Analysis of Integrated Data and Energy Transfer Assisted by Fluid Antenna Systems

Fluid antenna multiple access (FAMA) is capable of exploiting the high spatial diversity of wireless channels to mitigate multi-user interference via flexible port switching, which achieves a better performance than traditional multi-input-multi-output (MIMO) systems. Moreover, integrated data and energy transfer (IDET) is able to provide both the wireless data transfer (WDT) and wireless energy transfer (WET) services towards low-power devices. In this paper, a FAMA assisted IDET system is studied, where N access points (APs) provide dedicated IDET services towards N user equipments (UEs). Each UE is equipped with a single fluid antenna. The performance of WDT and WET, i.e., the WDT outage probability, the WET outage probability, the reliable throughput and the average energy harvesting amount, are analysed theoretically by using time switching (TS) between WDT and WET. Numerical results validate our theoretical analysis, which reveals that the number of UEs and TS ratio should be optimized to achieve a trade-off between the WDT and WET performance. Moreover, FAMA assisted IDET achieves a better performance in terms of both WDT and WET than traditional MIMO with the same antenna size

Performance Analysis of Slow Fluid Antenna Multiple Access in Noisy Channels using Gauss-Laguerre and Gauss-Hermite Quadratures

Fluid antenna system (FAS) facilitating a position-switchable antenna, enables a mobile receiver to exploit the deep fade opportunity of its interference for multiple access. Slow fluid antenna multiple access ( s -FAMA) is such an emerging proposal that lets multiple users share the same time-frequency channel while each user adopts a fluid antenna to resolve the interference. Previous performance analysis is limited to the case when noise is neglected. In this letter, we remove this limitation and derive new closed-form expressions for the outage probability of s -FAMA by using Gauss-Laguerre and Gauss-Hermite Quadratures. The analysis reveals the impact of noise on the outage probability for different numbers of users and ports in s -FAMA networks

Position Index Modulation for Fluid Antenna System

Fluid antenna system (FAS) represents all forms of movable and non-movable position-flexible antenna system, and opens up the possibility of a new form of modulation schemes. In this paper, we investigate the design of position index modulation (PIM) for FAS for decreasing the bit error rate (BER) while taking advantage of the rate gain in index modulation. We further derive the BER and data rate expressions to assess the achievable performance of PIM. Simulation results are provided to illustrate the performance and some insights are drawn into the impact of both channel estimation accuracy and transmission power

Rare Crustaceans from the Upper Devonian Chagrin Shale in Northern Ohio

47-64http://deepblue.lib.umich.edu/bitstream/2027.42/48384/2/ID229.pd

AoI-Aware Joint Resource Allocation in Multi-UAV Aided Multi-Access Edge Computing Systems

Compared with traditional latency, age of information (AoI) is regarded as a more sufficient metric to measure the freshness of information. In this paper, we investigate the AoI-aware unmanned aerial vehicle (UAV) aided multi-access edge computing (MEC) system, where the UAVs, equipped with MEC servers, provide computing service to the ground IoT devices, which have heterogeneous average peak AoI (APAoI) requirements. According to the Poisson process model, the probabilistic LoS channel model and the M/D/1 queue model, the APAoI of each IoT device is derived, which involves the hovering locations of the UAVs and the communication and computing resources. Then, considering the APAoI requirements of the IoT devices, we formulate the energy consumption minimization problem, in which the offloading strategy and the transmit power of the devices, and the communication and computing resources allocation as well as the hovering locations of the UAVs are jointly optimized. The formulated optimization problem is non-convex. To efficiently solve it, we decompose it into five subproblems and propose an alternative algorithm based on the traditional mathematical method, KKT conditions, and successive convex approximation technique. Extensive simulation results are provided to show the performance gain of the proposed algorithm

OPTIMALISASI LABA PERUSAHAAN DENGAN PENDEKATAN METODE LAGRANGE PADA COFFEE SHOP “SELOW TIME”

Penelitian ini bertujuan untuk mengoptimalkan laba Coffee Shop Selow Time melalui pendekatan matematika ekonomi menggunakan metode Lagrange Multiplier dalam fungsi produksi Cobb-Douglas. Dengan mempertimbangkan keterbatasan anggaran produksi, studi ini memformulasikan model matematis untuk menentukan kombinasi input modal dan tenaga kerja yang efisien. Melalui data simulasi, diperoleh hasil bahwa kombinasi modal sebesar 40 unit dan tenaga kerja 30 unit mampu menghasilkan output maksimum sebesar 72,13 unit dan laba bersih Rp6.213 dari total biaya Rp1.000. Pendekatan ini menunjukkan bahwa metode Lagrange dapat menjadi alat bantu manajerial yang efektif dalam pengambilan keputusan berbasis data, terutama bagi pelaku UMKM yang menghadapi keterbatasan sumber daya. Hasil penelitian ini menunjukkan bahwa metode Lagrange dapat menjadi alat bantu pengambilan keputusan yang efektif, khususnya bagi pelaku UMKM yang memiliki keterbatasan sumber daya. Selain itu, fungsi produksi Cobb-Douglas terbukti mampu merepresentasikan hubungan input-output yang realistis dalam sektor jasa seperti coffee shop