On the Throughput of Large-but-Finite MIMO Networks using Schedulers

This paper studies the sum throughput of the {multi-user} multiple-input-single-output (MISO) networks in the cases with large but finite number of transmit antennas and users. Considering continuous and bursty communication scenarios with different users' data request probabilities, we derive quasi-closed-form expressions for the maximum achievable throughput of the networks using optimal schedulers. The results are obtained in various cases with different levels of interference cancellation. Also, we develop an efficient scheduling scheme using genetic algorithms (GAs), and evaluate the effect of different parameters, such as channel/precoding models, number of antennas/users, scheduling costs and power amplifiers' efficiency, on the system performance. Finally, we use the recent results on the achievable rates of finite block-length codes to analyze the system performance in the cases with short packets. As demonstrated, the proposed GA-based scheduler reaches (almost) the same throughput as in the exhaustive search-based optimal scheduler, with substantially less implementation complexity. Moreover, the power amplifiers' inefficiency and the scheduling delay affect the performance of the scheduling-based systems significantly

Stochastic Cooperative Decision Approach for Studying the Symmetric Behavior of People in Wireless Indoor Location Systems

[EN] Nowadays, several wireless location systems have been developed in the research world. The goal of these systems has always been to find the greatest accuracy as possible. However, if every node takes data from the environment, we can gather a lot of information, which may help us understand what is happening around our network in a cooperative way. In order to develop this cooperative location and tracking system, we have implemented a sensor network to capture data from user devices. From this captured data we have observed a symmetry behavior in people's movements at a specific site. By using these data and the symmetry feature, we have developed a statistical cooperative approach to predict the new user's location. The system has been tested in a real environment, evaluating the next location predicted by the system and comparing it with the next location in the real track, thus getting satisfactory results. Better results have been obtained when the stochastic cooperative approach uses the transition matrix with symmetry.This work is supported by the "Universitat Politecnica de Valencia" through "PAID-05-12".Tomás Gironés, J.; García Pineda, M.; Canovas Solbes, A.; Lloret, J. (2016). Stochastic Cooperative Decision Approach for Studying the Symmetric Behavior of People in Wireless Indoor Location Systems. Symmetry (Basel). 8(7):1-13. https://doi.org/10.3390/sym8070061S11387Gu, Y., Lo, A., & Niemegeers, I. (2009). A survey of indoor positioning systems for wireless personal networks. IEEE Communications Surveys & Tutorials, 11(1), 13-32. doi:10.1109/surv.2009.090103Maghdid, H. S., Lami, I. A., Ghafoor, K. Z., & Lloret, J. (2016). Seamless Outdoors-Indoors Localization Solutions on Smartphones. ACM Computing Surveys, 48(4), 1-34. doi:10.1145/2871166Li, F., Zhao, C., Ding, G., Gong, J., Liu, C., & Zhao, F. (2012). 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On the symmetry of user mobility in wireless networks. 2011 IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks. doi:10.1109/wowmom.2011.5986146Deng, Z., Yu, Y., Yuan, X., Wan, N., & Yang, L. (2013). Situation and development tendency of indoor positioning. China Communications, 10(3), 42-55. doi:10.1109/cc.2013.6488829Lloret, J., Tomas, J., Garcia, M., & Canovas, A. (2009). A Hybrid Stochastic Approach for Self-Location of Wireless Sensors in Indoor Environments. Sensors, 9(5), 3695-3712. doi:10.3390/s90503695Feng, C., Au, W. S. A., Valaee, S., & Tan, Z. (2012). Received-Signal-Strength-Based Indoor Positioning Using Compressive Sensing. IEEE Transactions on Mobile Computing, 11(12), 1983-1993. doi:10.1109/tmc.2011.216Wang, J., Hu, A., Liu, C., & Li, X. (2015). A Floor-Map-Aided WiFi/Pseudo-Odometry Integration Algorithm for an Indoor Positioning System. Sensors, 15(4), 7096-7124. doi:10.3390/s150407096Dhruv Pandya, Ravi Jain, & Lupu, E. (s. f.). Indoor location estimation using multiple wireless technologies. 14th IEEE Proceedings on Personal, Indoor and Mobile Radio Communications, 2003. PIMRC 2003. doi:10.1109/pimrc.2003.1259108Garcia, M., Sendra, S., Lloret, J., & Canovas, A. (2011). Saving energy and improving communications using cooperative group-based Wireless Sensor Networks. Telecommunication Systems, 52(4), 2489-2502. doi:10.1007/s11235-011-9568-3Garcia, M., & Lloret, J. (2009). A Cooperative Group-Based Sensor Network for Environmental Monitoring. Cooperative Design, Visualization, and Engineering, 276-279. doi:10.1007/978-3-642-04265-2_41Patwari, N., Ash, J. N., Kyperountas, S., Hero, A. O., Moses, R. L., & Correal, N. S. (2005). Locating the nodes: cooperative localization in wireless sensor networks. IEEE Signal Processing Magazine, 22(4), 54-69. doi:10.1109/msp.2005.1458287Conti, A., Guerra, M., Dardari, D., Decarli, N., & Win, M. Z. (2012). Network Experimentation for Cooperative Localization. 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CCA Threshold Impact on the MAC Layer Performance in IoT Networks

International audienceWhile current medium access control solutions in low-power wide area networks are generally based on Aloha, recent studies demonstrated the interest of adding carrier sense mechanisms to the picture. In this paper, we investigate the impact of the carrier sense threshold parameter in this particular context. We show that its impact on the average behavior of the network is limited, but this changes when looking at the individual node performance. Our simulation results demonstrate an important heterogeneity among nodes, both in terms of packet success probability and of energy consumption. Moreover, the performance of the nodes is strongly correlated with the percentage of contending nodes that they can sense. By simply using two different carrier sense thresholds in the network, we achieve an increased fairness among nodes

Cooperation techniques between LTE in unlicensed spectrum and Wi-Fi towards fair spectral efficiency

On the road towards 5G, a proliferation of Heterogeneous Networks (HetNets) is expected. Sensor networks are of great importance in this new wireless era, as they allow interaction with the environment. Additionally, the establishment of the Internet of Things (IoT) has incredibly increased the number of interconnected devices and consequently the already massive wirelessly transmitted traffic. The exponential growth of wireless traffic is pushing the wireless community to investigate solutions that maximally exploit the available spectrum. Recently, 3rd Generation Partnership Project (3GPP) announced standards that permit the operation of Long Term Evolution (LTE) in the unlicensed spectrum in addition to the exclusive use of the licensed spectrum owned by a mobile operator. Alternatively, leading wireless technology developers examine standalone LTE operation in the unlicensed spectrum without any involvement of a mobile operator. In this article, we present a classification of different techniques that can be applied on co-located LTE and Wi-Fi networks. Up to today, Wi-Fi is the most widely-used wireless technology in the unlicensed spectrum. A review of the current state of the art further reveals the lack of cooperation schemes among co-located networks that can lead to more optimal usage of the available spectrum. This article fills this gap in the literature by conceptually describing different classes of cooperation between LTE and Wi-Fi. For each class, we provide a detailed presentation of possible cooperation techniques that can provide spectral efficiency in a fair manner

MSE minimized joint transmission in coordinated multipoint systems with sparse feedback and constrained backhaul requirements

In a joint transmission coordinated multipoint (JT-CoMP) system, a shared spectrum is utilized by all neighbor cells. In the downlink, a group of base stations (BSs) coordinately transmit the users’ data to avoid serious interference at the users in the boundary of the cells, thus substantially improving area fairness. However, this comes at the cost of high feedback and backhaul load; In a frequency division duplex system, all users at the cell boundaries have to collect and send feedback of the downlink channel state information (CSI). In centralized JT-CoMP, although with capabilities for perfect coordination, a central coordination node have to send the computed precoding weights and corresponding data to all cells which can overwhelm the backhaul resources. In this paper, we design a JT-CoMP scheme, by which the sum of the mean square error (MSE) at the boundary users is minimized, while feedback and backhaul loads are constrained and the load is balanced between BSs. Our design is based on the singular value decomposition of CSI matrix and optimization of a binary link selection matrix to provide sparse feedback—constrained backhaul link. For comparison, we adopt the previously presented schemes for feedback and backhaul reduction in the physical layer. Extensive numerical evaluations show that the proposed scheme can reduce the MSE with at least 25 % , compared to the adopted and existing schemes

Time-shifted Pilot-based Scheduling with Adaptive Optimization for Pilot Contamination Reduction in Massive MIMO, Journal of Telecommunications and Information Technology, 2020, nr 4

Massive multiple-input multiple-output (MIMO) is considered to be an emerging technique in wireless communication systems, as it offers the ability to boost channel capacity and spectral efficiency. However, a massive MIMO system requires huge base station (BS) antennas to handle users and suffers from inter-cell interference that leads to pilot contamination. To cope with this, time-shifted pilots are devised for avoiding interference between cells, by rearranging the order of transmitting pilots in different cells. In this paper, an adaptive-elephant-based spider monkey optimization (adaptive ESMO) mechanism is employed for time-shifted optimal pilot scheduling in a massive MIMO system. Here, user grouping is performed with the sparse fuzzy c-means (Sparse FCM) algorithm, grouping users based on such parameters as large-scale fading factor, SINR, and user distance. Here, the user grouping approach prevents inappropriate grouping of users, thus enabling effective grouping, even under the worst conditions in which the channel operates. Finally, optimal time-shifted scheduling of the pilot is performed using the proposed adaptive ESMO concept designed by incorporating adaptive tuning parameters. The efficiency of the adaptive ESMO approach is evaluated and reveals superior performance with the highest achievable uplink rate of 43.084 bps/Hz, the highest SINR of 132.9 dB, and maximum throughput of 2.633 Mbp

Self-organized Clustering for Improved Interference Mitigation in White Spaces, Journal of Telecommunications and Information Technology, 2017, nr 2

In this paper a collaborative coexistence mechanism for white space base stations is proposed. We look at the case where these base stations operate in geographical areas where the density of used TV channels is such that only one channel is left for broadband access. We show how with cooperative closed loop control and a clustering strategy, it is possible to find feasible power assignments that provide a flexible and stable coverage solution. The framework under which we study our proposal is based on the IEEE 802.22 standard, which provides white space guidelines for applications in broadband access or machine-to-machine communications. We propose and evaluate a self-organized, collaborative power control and design strategy to enable effective coexistence of base stations under extreme bandwidth constraints. Finally, we also portray how proposed approach positively compares against others from different wireless access technologies

Secrecy Rate Region Enhancement in Multiple Access Wiretap Channel, Journal of Telecommunications and Information Technology, 2022, nr 2

It is commonly known that physical layer security is achieved with a trade-off in terms of the achievable rate. Hence, security constraints generate rate losses in wiretap channels. To mitigate such rate losses in multi-user channels, we propose a coding/decoding scheme for multi-user multiple access wiretap channel (MAC-WT), where previously transmitted messages are used as a secret key to enhance the secrecy rates of the transmitting users, until the usual Shannon capacity region of a multiple access channel (MAC) is achieved without the secrecy constraint. With this coding scheme, all messages transmitted in the recent past are secure with respect to all the information of the eavesdropper till now. To achieve this goal, we introduce secret key buffers at both the users and the legitimate receiver. Finally, we consider a fading MAC-WT and show that with this coding/decoding scheme, we can achieve the capacity region of a fading MAC channel (in the ergodic sense)

Enhancing the performance of energy harvesting wireless communications using optimization and machine learning

The motivation behind this thesis is to provide efficient solutions for energy harvesting communications. Firstly, an energy harvesting underlay cognitive radio relaying network is investigated. In this context, the secondary network is an energy harvesting network. Closed-form expressions are derived for transmission power of secondary source and relay that maximizes the secondary network throughput. Secondly, a practical scenario in terms of information availability about the environment is investigated. We consider a communications system with a source capable of harvesting solar energy. Two cases are considered based on the knowledge availability about the underlying processes. When this knowledge is available, an algorithm using this knowledge is designed to maximize the expected throughput, while reducing the complexity of traditional methods. For the second case, when the knowledge about the underlying processes is unavailable, reinforcement learning is used. Thirdly, a number of learning architectures for reinforcement learning are introduced. They are called selector-actor-critic, tuner-actor-critic, and estimator-selector-actor-critic. The goal of the selector-actor-critic architecture is to increase the speed and the efficiency of learning an optimal policy by approximating the most promising action at the current state. The tuner-actor-critic aims at improving the learning process by providing the actor with a more accurate estimation about the value function. Estimator-selector-actor-critic is introduced to support intelligent agents. This architecture mimics rational humans in the way of analyzing available information, and making decisions. Then, a harvesting communications system working in an unknown environment is evaluated when it is supported by the proposed architectures. Fourthly, a realistic energy harvesting communications system is investigated. The state and action spaces of the underlying Markov decision process are continuous. Actor-critic is used to optimize the system performance. The critic uses a neural network to approximate the action-value function. The actor uses policy gradient to optimize the policy\u27s parameters to maximize the throughput