Weiping Sun

Wi-Fi could be much more

Wi-Fi has become an essential wireless technology in our daily lives, although the original intention of its introduction was to replace Ethernet cable. In this article, we outline the most remarkable features introduced during its ongoing technological evolution in terms of three major directions: throughput enhancement, longrange extension, and greater ease of use. By stitching these advanced features together, we also envision a promising future that Wi-Fi technology will bring us in terms of spectrum heterogeneity, seamless service provisioning, and possible relations with cellular networks.

Reliable Video Multicast over Wi-Fi Networks with Coordinated Multiple APs

Forward Error Correction (FEC) can be exploited to realize reliable video multicast over Wi-Fi with high video quality. We propose reliable video multicast over Wi-Fi networks with coordinated multiple Access Points (APs) to enhance video quality. By coordinating multiple APs, each AP can transmit entirely or partially different FEC-encoded packets so that a multicast receiver can benefit from both spatial and time diversities. The proposed schemes can enlarge the satisfactory video multicast region by exploiting the AP diversity, thus serving more multicast receivers located at cell edge with satisfactory video quality. We propose a resource-allocation algorithm for FEC-code rate adaptation, utilizing the limited wireless resource more efficiently while enhancing video quality. We also introduce the method for estimating the video packet delivery ratio after FEC decoding. The effectiveness of the proposed schemes is comparatively evaluated via extensive simulation and experimentation. The proposed schemes are observed to enhance the ratio of satisfied users by up to 37.1% compared to the conventional single AP multicast scheme.

COTA: Channel occupancy time adaptation for LTE in unlicensed spectrum

LTE operation in unlicensed spectrum is emerging as a promising technology in achieving higher data rate with LTE since ultra-wide unlicensed spectrum, e.g., about 500 MHz at 5–6 GHz range, is available in most countries. Recently, 3GPP has finalized standardization of licensed assisted access (LAA) for LTE operation in 5 GHz unlicensed spectrum, which has been a playground only for Wi-Fi. LAA defines downlink transmission over 5 GHz spectrum, where channel sensing, i.e., listen before talk (LBT) operation similar to Wi-Fi medium access control (MAC) protocol, is performed before each transmission of eNodeB. LAA has a fixed 8 ms maximum channel occupancy time (COT), which is the maximum continuous transmission time after channel sensing, while Wi-Fi may transmit for much shorter time duration. As a result, when Wi-Fi coexists with LAA, Wi-Fi airtime and throughput can be much less than those achieved when Wi-Fi coexists with another Wi-Fi. To guarantee fair airtime and improve throughput of Wi-Fi, we propose a COT adaptation (COTA) algorithm, which observes Wi-Fi aggregate MAC protocol data unit (A-MPDU) frames and matches LAAs COT to the duration of A-MPDU frames. Moreover, COTA detects saturation of Wi-Fi traffic and adjusts COT only if Wi-Fi traffic is saturated. We prototype saturation detection algorithm of COTA with commercial off-the-shelf Wi-Fi device and show that COTA detects saturation of Wi-Fi networks accurately. Through ns-3 simulations, we demonstrate that COTA achieves up to 153% Wi-Fi throughput gain while providing airtime fairness between LAA and Wi-Fi.

ChASER: Channel-aware symbol error reduction for high-performance WiFi systems in dynamic channel environment

Due to considerable increases in user mobility and frame length through aggregation, the wireless channel remains no longer time-invariant during the (aggregated) frame transmission time. However, the existing IEEE 802.11 standards still define the channel estimation to be performed only once at the preamble for coherent OFDM receivers, and the same channel information to be used throughout the entire (aggregated) frame processing. Our experimental results reveal that this baseline channel estimation approach seriously deteriorates the WiFi performance, especially for pedestrian mobile users and the recently adopted frame aggregation scheme. In this paper, we propose Channel-Aware Symbol Error Reduction (ChASER), a new practical channel estimation and tracking scheme for WiFi receivers. ChASER utilizes the re-encoding and re-modulation of the received data symbol to keep up with the wireless channel dynamics at the granularity of OFDM symbols. Our extensive, trace-driven link-level simulation shows significant performance gains over a wide range of channel conditions based on the real wireless channel traces collected by the off-the-shelf WiFi device. In addition, the feasibility of its low-complexity and standard compliance is demonstrated by Microsofts Software Radio (Sora) prototype implementation and experimentation. To our knowledge, ChASER is the first IEEE 802.11n-compatible channel tracking algorithm since other approaches addressing the time-varying channel conditions over a single (aggregated) frame duration require costly modifications of the IEEE 802.11n standard.

Listen channel randomization for faster Wi-Fi direct device discovery

Wi-Fi Direct, now part of Android smartphones, makes it possible for Wi-Fi devices to communicate directly without passing through an access point. Before starting actual data exchange, two devices should apparently find each other through a device discovery process, called find phase. After identifying the limitation of the legacy find phase, incurring long discovery delay, we propose a simple and efficient scheme, called Listen Channel Randomization (LCR), in order to expedite device discovery. Both the legacy find phase and LCR are evaluated with our elaborate Markov model and ns-3 simulations for comprehensive comparisons. Moreover, we have implemented a prototype of LCR in Android smartphone. Our experimental results reveal that LCR can significantly reduce the device discovery delay, yielding up to 72% delay reduction compared to the legacy find phase.

CV-Track: Leveraging Carrier Frequency Offset Variation for BLE Signal Detection

We propose CV-Track, a real-time, low-complexity BLE signal detection scheme that leverages carrier frequency offset (CFO) estimation of commodity BLE chipsets to enable detection of the intact part of a partially corrupted BLE packet. It detects BLE signal by observing the variation of the estimated CFO values based on the finding that the CFO values are almost constant for BLE signal while dispersing otherwise. With CV-Track, we can salvage useful information such as received signal strength from an erroneous BLE packet which would otherwise be wasted. We implement a prototype of CV-Track on commodity BLE chipset and evaluate its performance in an indoor environment. Our results indicate that CV-Track detects significantly more BLE packets compared with legacy BLE receiver under cross-technology interference.

Performance Analysis of LTE-LAA Network

3rd generation partnership project (3GPP) has developed 5-GHz unlicensed band long term evolution (LTE), referred to as licensed-assisted access (LAA). LAA adopts listen-before-talk (LBT) operation, resembling Wi-Fi’s carrier sense multiple access with collision avoidance (CSMA/CA), to enable collision avoidance capability. However, the frame structure overhead of each LAA downlink burst varies with the ending time of each preceding LBT operation. Given that, the existing analytic models of Wi-Fi cannot be used to evaluate the performance of LAA due to the fact that, unlike Wi-Fi, LAA frame structure overhead varies with the ending time of the preceding LBT operation. In this letter, we propose a novel Markov chain-based analytic model to cope with the variation of the LAA frame structure overhead. Comparison between analysis and simulation results shows that the difference between them is merely 0.2% on average, demonstrating the accuracy of the proposed model.

BlueCoDE: Bluetooth coordination in dense environment for better coexistence

Dense Wi-Fi and Bluetooth (BT) environments become increasingly common so that the coexistence issue between Wi-Fi and BT is imperative to solve. In this paper, we propose BlueCoDE, a coordination scheme for multiple neighboring BT piconets, to make them collision-free and less harmful to Wi-Fi. BlueCoDE reuses BTs existing PHY and MAC design, thus making it practically feasible. We implement a prototype of BlueCoDE on Ubertooth One platform and corroborate the performance gain via analysis, NS-3 simulations, and prototype-based experiments. Our experimental results show that with merely 10 legacy BT piconets, neighboring Wi-Fi network becomes useless achieving under 1 Mb/s throughput, while BlueCoDE enables the Wi-Fi throughput always remain above 12 Mb/s. We expect BlueCoDE to be a breakthrough solution for coexistence in dense Wi-Fi and BT environments.