The IEEE 802.11ac is an emerging very high throughput (VHT) WLAN standard that could achieve PHY data rates of close to 7 Gbps for the 5 GHz band. In this paper, we introduce the key mandatory and optional PHY features, as well as the MAC enhancements of 802.11ac over the existing 802.11n standard in the evolution towards higher data rates. Through numerical analysis and simulations, we compare the MAC performance between 802.11ac and 802.11n over three different frame aggregation mechanisms, viz., aggregate MAC service data unit (A-MSDU), aggregate MAC protocol data unit (A-MPDU), and hybrid A-MSDU/A-MPDU aggregation. Our results indicate that 802.11ac with a configuration of 80MHz and single (two) spatial stream(s) outperforms 802.11n with a configuration of 40 MHz and two spatial streams in terms of maximum throughput by 28% (84%). In addition, we demonstrate that hybrid A-MSDU/A-MPDU aggregation yields the best performance for both 802.11n and 802.11ac devices, and its improvement is a function of the maximum A-MSDU size.

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IEEE 802.11ac: Enhancements for very high throughput WLANs

For uplink large-scale multiple-input–multiple-output (MIMO) systems, the minimum mean square error (MMSE) algorithm is near optimal but involves matrix inversion with high complexity. In this paper, we propose to exploit the Gauss–Seidel (GS) method to iteratively realize the MMSE algorithm without the complicated matrix inversion. To further accelerate the convergence rate and reduce the complexity, we propose a diagonal-approximate initial solution to the GS method, which is much closer to the final solution than the traditional zero-vector initial solution. We also propose an approximated method to compute log-likelihood ratios for soft channel decoding with a negligible performance loss. The analysis shows that the proposed GS-based algorithm can reduce the computational complexity from ${{\mathcal O}({K^3})}$ to ${{\mathcal O}({K^2})}$ , where ${K}$ is the number of users. Simulation results verify that the proposed algorithm outperforms the recently proposed Neumann series approximation algorithm and achieves the near-optimal performance of the classical MMSE algorithm with a small number of iterations.

Low-Complexity Soft-Output Signal Detection Based on Gauss–Seidel Method for Uplink Multiuser Large-Scale MIMO Systems

For uplink large-scale MIMO systems, minimum mean square error (MMSE) algorithm is near-optimal but involves matrix inversion with high complexity. In this paper, we propose to exploit the Gauss-Seidel (GS) method to iteratively realize the MMSE algorithm without the complicated matrix inversion. To further accelerate the convergence rate and reduce the complexity, we propose a diagonal-approximate initial solution to the GS method, which is much closer to the final solution than the traditional zero-vector initial solution. We also propose a approximated method to compute log-likelihood ratios (LLRs) for soft channel decoding with a negligible performance loss. The analysis shows that the proposed GS-based algorithm can reduce the computational complexity from O(K^3) to O(K^2), where K is the number of users. Simulation results verify that the proposed algorithm outperforms the recently proposed Neumann series approximation algorithm, and achieves the near-optimal performance of the classical MMSE algorithm with a small number of iterations.

Low-Complexity Soft-Output Signal Detection Based on Gauss-Seidel Method for Uplink Multi-User Large-Scale MIMO Systems

Latency is increasingly becoming a performance bottleneck for Internet Protocol (IP) networks, but historically, networks have been designed with aims of maximizing throughput and utilization. This paper offers a broad survey of techniques aimed at tackling latency in the literature up to August 2014, as well as their merits. A goal of this work is to be able to quantify and compare the merits of the different Internet latency reducing techniques, contrasting their gains in delay reduction versus the pain required to implement and deploy them. We found that classifying techniques according to the sources of delay they alleviate provided the best insight into the following issues: 1) The structural arrangement of a network, such as placement of servers and suboptimal routes, can contribute significantly to latency; 2) each interaction between communicating endpoints adds a Round Trip Time (RTT) to latency, particularly significant for short flows; 3) in addition to base propagation delay, several sources of delay accumulate along transmission paths, today intermittently dominated by queuing delays; 4) it takes time to sense and use available capacity, with overuse inflicting latency on other flows sharing the capacity; and 5) within end systems, delay sources include operating system buffering, head-of-line blocking, and hardware interaction. No single source of delay dominates in all cases, and many of these sources are spasmodic and highly variable. Solutions addressing these sources often both reduce the overall latency and make it more predictable.

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Reducing Internet Latency: A Survey of Techniques and Their Merits

The IEEE 802.11-based WiFi wireless technology is one of the most promising technologies to provide ubiquitous networking access. The IEEE 802.11 working group has always strived to improve this wireless technology through creating new amendments to the base 802.11 standard. Recently, IEEE 802.11n amendment was created to enhance 802.11 for higher throughput operation. Not only new Physical Layer enhancements are standardized, but new Medium Access Control Layer mechanism are also defined. In this paper, we examine the network performance enhancement by the proposed 802.11n MAC layer features: aggregation, block acknowledgement, and reverse direction mechanism. We implemented a new 802.11n module in the NS-2 simulation platform. The simulation results demonstrated the effectiveness of 802.11n MAC layer enhancement. VoIP performance is effectively improved with 802.11n MAC enhancement.

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IEEE 802.11n MAC Enhancement and Performance Evaluation

IEEE 802.11n is an ongoing next-generation wireless LAN standard that supports a very highspeed connection with more than 100 Mb/s data throughput measured at the medium access control layer. This article investigates the key MAC enhancements that help 802.11n achieve high throughput and high efficiency. A detailed description is given for various frame aggregation mechanisms proposed in the latest 802.11n draft standard. Our simulation results confirm that A-MSDU, A-MPDU, and a combination of these methods improve extensively the channel efficiency and data throughput. We analyze the performance of each frame aggregation scheme in distinct scenarios, and we conclude that overall, the two-level aggregation is the most efficacious.

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IEEE 802.11n MAC frame aggregation mechanisms for next-generation high-throughput WLANs

In this paper we investigate potential benefits that an adaptive delayed channel access algorithm can attain for the next-generation wireless LANs, the IEEE 802.11n. We show that the performance of frame aggregation introduced by the 802.11n adheres due to the priority mechanism of the legacy 802.11e EDCA scheduler, resulting in a poor overall performance. Because high priority flows have low channel utilization, the low priority flows throughputs can be amerced further. By introducing an additional delay at the MAC layer, before the channel access scheduling, it will retain aggregate sizes at higher numbers and consequently a better channel utilization. Also, in order to support both UDP and TCP transport layer protocols, the algorithm's operational conditions are kept adaptive. The simulation results demonstrate that our proposed adaptive delayed channel access outperforms significantly the current 802.1 In specification and non-adaptive delayed channel access.

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Adaptive Delayed Channel Access for IEEE 802.11n WLANs

In this paper we investigate the potential benefits of a selective delayed channel access algorithm (SDCA) for the future IEEE 802.11n based high-throughput networks. The proposed solution aims to resolve the poor channel utilization and the low efficiency that EDCA's high priority stations adhere due to shorter waiting times and consequently to the network's degrading overall end performance. The algorithm functions at the MAC level where it delays the packets from being transmitted by postponing the channel access request, based on their traffic characteristics. As a result, the flow's average aggregate size increases and consequently so is the channel efficiency. However, in some situations we notice that further deferring has a negative impact with TCP applications, thus we further introduce a traffic awareness feature that allows the algorithm to distinguish which flows are using the TCP protocol and override any additional MAC delay. We validate through various simulations that SDCA improves throughput significantly and maximizes channel utilization.

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D. Skordoulis

Papers

IEEE 802.11n MAC frame aggregation mechanisms for next-generation high-throughput WLANs

Adaptive Delayed Channel Access for IEEE 802.11n WLANs

A Selective Delayed Channel Access (SDCA) for the High-Throughput IEEE 802.11n