5 research outputs found

    QoS-based Joint User Selection and Scheduling for MU-MIMO WLANs, Journal of Telecommunications and Information Technology, 2017, nr 4

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    The shift in Multi-User Multiple Input Multiple Output (MU-MIMO) has gained attention due to its wide support in very high throughput Wireless Local Area Networks (WLANs) such as the 802.11ac. However, the full advantage of MU-MIMO can be utilized only with proper user selection and scheduling. Also, providing Quality of Service (QoS) support is a major challenge for these wireless networks. Generally, user scheduling is done with the acquisition of Channel State Information (CSI) from all the users. In MU-MIMO based WLANs, the number of CSI request increases with the number of users. This results in an increased CSI overhead and in degradation of the overall throughput. Most of the proposals in the literature have not addressed the contention in the CSI feedback clearly. Hence, in this paper a Joint User Selection and Scheduling (JUSS) scheme is discussed and its performance is evaluated in terms of throughput, delay, packet loss and fairness. In the performance comparison some wellknown Medium Access Control (MAC) protocols are considered. The proposed scheme not only enhances throughput, but also avoids contention during CSI feedback period

    Optimal ALOHA-like random access with heterogeneous QoS guarantees for multi-packet reception aided visible light communications

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    There is a paucity of random access protocols designed for alleviating collisions in visible light communication (VLC) systems where carrier sensing is hard to be achieved due to the directionality of light. To resolve the problem of collisions, we adopt the successive interference cancellation (SIC) algorithm to enable the coordinator to simultaneously communicate with multiple devices, which is referred to as the multi-packet reception (MPR) capability. However, the MPR capability could be fully utilized only when random access algorithms are accordingly designed. Considering the characteristics of the random access VLC system with SIC, we propose a novel effective capacity (EC)-based ALOHA-like random access algorithm for MPR-aided uplink VLC systems having heterogeneous quality-of-service (QoS) guarantees. Firstly, we model the VLC network as a conflict graph and derive the EC for each device. Then, we formulate the VLC QoS-driven random access problem as a saturation throughput maximization problem subject to multiple statistical QoS constraints. Finally, the resultant non-concave optimization problem (OP) is solved by a memetic search algorithm relying on invasive weed optimization and differential evolution (IWO-DE). We demonstrate that our derived EC expression matches the Monte Carlo simulation results accurately, and the performance of our proposed algorithm is competitive

    QoS based Radio Resource Management Techniques for Next Generation MU-MIMO WLANs: A Survey

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    IEEE 802.11 based Wireless Local Area Networks (WLANs) have emerged as a popular candidate that offers Internet services for wireless users. The demand of data traffic is increasing every day due to the increase in the use of multimedia applications, such as digital audio, video, and online gaming. With the inclusion of Physical Layer (PHY) technologies, such as the OFDM and MIMO, the current 802.11ac WLANs are claiming Gigabit speeds. Hence, the existing Medium Access Control (MAC) must be in a suitable position to convert the offered PHY data rates for efficient throughput. Further, the integration of cellular networks with WLANs requires unique changes at MAC layer. It is highly required to preserve the Quality of Service (QoS) in these scenarios. Fundamentally, many QoS issues arise from the problem of effective Radio Resource Management (RRM). Although IEEE 802.11 has lifted PHY layer aspects, there is a necessity to investigate MAC layer issues, such as resource utilization, scheduling, admission control and congestion control. In this survey, a literature overview of these techniques, namely the resource allocation and scheduling algorithms are briefly discussed in connection with the QoS at MAC layer. Further, some anticipated enhancements proposed for Multi-User Multiple-Input and Multiple-Output (MU-MIMO) WLANs are discussed

    Low-Complexity Multi-User MIMO Algorithms for mmWave WLANs

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    Very high throughput and high-efficiency wireless local area networks (WLANs) have become essential for today's significant global Internet traffic and the expected significant global increase of public WiFi hotspots. Total Internet traffic is predicted to expand 3.7-fold from 2017 to 2022. In 2017, 53% of overall Internet traffic used by WiFi networks, and that number is expected to increase to 56.8% by 2022. Furthermore, 80% of overall Internet traffic is expected to be video traffic by 2022, up from 70% in 2017. WiFi networks are also expected to move towards denser deployment scenarios, such as stadiums, large office buildings, and airports, with very high data rate applications, such as ultra-high definition video wireless streaming. Thus, in order to meet the predicted growth of wireless traffic and the number of WiFi networks in the world, an efficient Internet access solution is required for the current IEEE 802.11 standards. Millimeter wave (mmWave) communication technology is expected to play a crucial role in future wireless networks with large user populations because of the large spectrum band it can provide. To further improve spectrum efficiency over mmWave bands in WLANs with large numbers of users, the IEEE 802.11ay standard was developed from the traditional IEEE 802.11ad standard, aiming to support multi-user MIMO. Propagation challenges associated with mmWave bands necessitate the use of analog beamforming (BF) technologies that employ directional transmissions to determine the optimal sector beam between a transmitter and a receiver. However, the multi-user MIMO is not exploited, since analog BF is limited to a single-user, single-transmission. The computational complexity of achieving traditional multi-user MIMO BF methods, such as full digital BF, in the mmWave systems becomes significant due to the hardware constraints. Our research focuses on how to effectively and efficiently realize multi-user MIMO transmission to improve spectrum efficiency over the IEEE 802.11ay mmWave band system while also resolving the computational complexity challenges for achieving a multi-user MIMO in mmWave systems. This thesis focuses on MAC protocol algorithms and analysis of the IEEE 802.11ay mmWave WLANs to provide multi-user MIMO support in various scenarios to improve the spectrum efficiency and system throughput. Specifically, from a downlink single-hop scenario perspective, a VG algorithm is proposed to schedule simultaneous downlink transmission links while mitigating the multi-user interference with no additional computational complexity. From a downlink multi-hop scenario perspective, a low-complexity MHVG algorithm is conducted to realize simultaneous transmissions and improve the network performance by taking advantage of the spatial reuse in a dense network. The proposed MHVG algorithm permits simultaneous links scheduling and mitigates both the multi-user interference and co-channel interference based only on analog BF information, without the necessity for feedback overhead, such as channel state information (CSI). From an uplink scenario perspective, a low-complexity user selection algorithm, HBF-VG, incorporates user selection with the HBF algorithm to achieve simultaneous uplink transmissions for IEEE 802.11ay mmWave WLANs. With the HBF-VG algorithm, the users can be selected based on an orthogonality criterion instead of collecting CSI from all potential users. We optimize the digital BF to mitigate the residual interference among selected users. Extensive analytical and simulation evaluations are provided to validate the performance of the proposed algorithms with respect to average throughput per time slot, average network throughput, average sum-rate, energy efficiency, signal-to-interference-plus-noise ratio (SINR), and spatial multiplexing gain
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