Indoor experiments on real-time multiuser MIMO transmission in wireless LAN systems

In this paper, we present robust joint non-linear transceiver designs for multiuser multiple-input multiple-output (MIMO) downlink in the presence of imperfections in the channel state information at the transmitter (CSIT). The base station (BS) is equipped with multiple transmit antennas, and each user terminal is equipped with one or more receive antennas. The BS employs Tomlinson-Harashima precoding (THP) for inter-user interference pre-cancellation at the transmitter. We consider robust transceiver designs that jointly optimize the transmit THP filters and receive filter for two models of CSIT errors. The first model is a stochastic error (SE) model, where the CSIT error is Gaussian-distributed. This model is applicable when the CSIT error is dominated by channel estimation error. In this case, the proposed robust transceiver design seeks to minimize a stochastic function of the sum mean square error (SMSE) under a constraint on the total BS transmit power. We propose an iterative algorithm to solve this problem. The other model we consider is a norm-bounded error (NBE) model, where the CSIT error can be specified by an uncertainty set. This model is applicable when the CSIT error is dominated by quantization errors. In this case, we consider a worst-case design. For this model, we consider robust i) minimum SMSE, ii) MSE-constrained, and iii) MSE-balancing transceiver designs. We propose iterative algorithms to solve these problems, wherein each iteration involves a pair of semi-definite programs (SDP). Further, we consider an extension of the proposed algorithm to the case with per-antenna power constraints.

TCP has been a congestion control method in the Internet. However, since TCP is not able to directly measure the network status from the end nodes, the TCP window control gradually increases the congestion window size until congestion occurs. This control gets network bandwidth aggressively and affects communication of all stations (STAs) which belong to the same access point of IEEE 802.11 standards. Especially, the communication quality for real-time applications such as video streaming becomes worse. To improve this problem, we have proposed a TCP window control method with adjusting the congestion window size for available bandwidth of the access point. TCP window size is adequately controlled by measuring the channel occupancy of each STA. The channel status information is passed to the TCP window control function via a cross layer control mechanism. We have developed a testbed and shown the effectiveness of our method by empirical evaluations.

In an infrastructure wireless LAN, the access point (AP) is responsible for connecting mobile stations (STA) and wired stations. Each access point is assigned on one channel. Traditionally, one station selects AP to connect is based on the received signal strength indicator (RSSI). This approach may cause all active mobile stations to connect to few APs and lots of contentions/collisions will occur by the Carrier Sense Multiple Access/Collision Avoidance (CSMA/CA) protocol. Consequently, the total network throughput will be degraded. Contrarily, if all STAs can be equally distributed to all APs and the signal strength of any pair of STA and connected AP is still kept in an acceptable range, the spare bandwidth in wireless LAN (WLAN) will be utilized in a more efficient way. In this paper, a novel dynamic load balance algorithm is proposed for WLAN. Simulation results show the proposed algorithm has the ability to fairly distribute all STAs among APs. Moreover, it also maximizes the average RSSI between AP and connected STAs.

Network densification through the deployment of WiFi access points (APs) is a promising solution towards achieving high connectivity rates required for emerging applications. A critical first step is to discover an AP before an active association between the client and the AP can be established. Legacy AP discovery procedures initiated by the client result in high latency in the order of a few 100 ms and waste spectrum, especially when clients need to frequently switch between multiple APs. We propose CSIscan that exploits the broadcast nature of WiFi channels by embedding discovery related information within an AP’s ongoing regular transmissions. The AP does this by intelligently distorting the transmitted OFDM frame by inducing perturbations in the preamble, and these injected ‘bits’ of information are detected via changes in the perceived channel state information (CSI). A deep learning framework allocates the optimal level of distortion on a per-subcarrier basis that keeps the resulting packet error rate to less than 1%. Existing clients perceive no changes in their ongoing communication, while potential new clients quickly obtain discovery information at the same time. We experimentally demonstrate that CSIscan reduces the overall WiFi latency from 150 ms to 10 ms and improves spectrum utilization with ~72% reduction in the probe traffic. We show that CSIscan delivers up to 40 discovery information bits in the outgoing WiFi packet in an indoor environment.

Fair and efficient resource allocation in IEEE 802.11ah WLAN with heterogeneous data rates

This paper deals with the problem of optimal association of stations (STAs) to access points (APs) for mulicast services in IEEE 802.11 WLAN. In a multicast session, all the subscribed STAs receive the multicast data packet at the same data rate (R min ) from their respective serving APs. A higher value of R min improves the multicast throughput by completing the ongoing multicast session in lesser time. This also improves the unicast throughput as the cycle duration is shared by the unicast and multicast sessions. To provide multicast services to the STAs, we need to select a minimum cardinality subset of APs as the system message overhead depends on this cardinality. However, such a minimum cardinality subset of APs may not be possible to activate simultaneously due to the limited number of available orthogonal frequency channels. In this paper, we develop a combined greedy algorithm that selects a subset of APs with minimum cardinality for which a conflict-free frequency assignment exists and finds an association between the STAs and the selected APs that maximizes the R min value. Through simulation we have shown that the proposed algorithm selects significantly less number of APs for different R min values in comparison to the well-known metrics for multicast association like RSSI, minimum hop-distance, normalized-cost and in-range STA number.

The feasibility of implementing non-orthogonal multiple access (NOMA) in massive multiple-input multiple-output (MIMO) downlink with distributed antenna arrays is investigated. The achievable downlink rates are derived for two channel state information (CSI) cases, namely (i) estimated uplink CSI at the access points (APs) via user uplink pilots and statistical CSI at the users, and (ii) estimated uplink CSI at the APs via uplink user pilots and estimated downlink CSI at the users via downlink pilots beamformed by the APs. The trade-off between the number of served user nodes and their achievable rates is investigated. The adverse effects of imperfect successive interference cancellation (SIC) and detection uncertainty on the achievable downlink rates are quantified. We show that the achievable downlink rate of NOMA can be inferior to that of the orthogonal multiple-access (OMA) counterpart in the low-user regime. This is a direct consequence of residual interference caused by intra-cluster pilot contamination and error propagation from imperfect SIC. However, the proposed massive MIMO NOMA downlink outperforms the OMA counterpart in the highuser regime in terms of the achievable downlink rate. Moreover, the impact of downlink pilots on the sum rate is also investigated.

Large Wi-Fi installations may make use of Wi-Fi controllers managing client mobility and different Virtual Local Area Networks (VLANs). However, as they might form a bottleneck, controller-less solutions are on the rise, e.g., cloud-managed solutions or mesh networks. IEEE 802.11 defines a framework for providing roaming assistance through neighbor reports and transition requests (IEEE 802.11k and IEEE 802.11v), but leaves generating meaningful candidates included in these frames open to the implementor. Without central controllers, deriving these candidates for Stations (STAs) is much more difficult. Access Points (APs) with more autonomy need to know other APs located in their proximity to provide roaming assistance for STAs. In this paper, we design and evaluate a network-assisted roaming architecture for controller-less Wi-Fi networks. APs learn roaming events in their vicinity and steer STAs by means of refined, yet standard-compliant neighbor reports and transition requests to better suited APs. Our results using a real-system prototype indicate a noticeable decrease of roaming times when comparing various reference approaches to our proposal.

The prevalence of WiFi infrastructures has enabled the advancement of a wide range of WiFi-based intelligent applications. Behavioral sensing, as an increasingly popular example, is attracting growing research interest in developing a device-free, accurate, and privacy-friendly interaction. Recent advances in behavioral research have shown great promise, but most of existing systems fail to capture the full scope of the relationship between WiFi signals and behaviors. In this work, we propose a behavioral sensing framework by modeling channel state information (CSI) of WiFi signals. The key insight is to harness antenna diversity and model signals reflected off the human body from multiple WiFi access points (APs) to infer daily activities. To this end, a CSI tensor is first constructed by aggregating the CSI from all WiFi APs. Next, a CANDECAMP/PARAFAC (CP) approach is leveraged for factorizing this CSI tensor into several single-rank tensors as key features. Then, a features optimization strategy is applied to the extracted features for selecting those correlated and dominant features by an embedded graph learning and constraint. Finally, a recurrent neural network (RNN) model is used to take the optimized features and capture a robust mapping between the input and output for recognizing daily activities in homes without requiring a prior calibration and any explicit involvement from the users. We design and implement a behavioral sensing prototype reusing existing WiFi and then carry out comprehensive experiments in two indoor environments. Extensive experimental results suggest that our scheme can accurately and effectively recognize the users’ behaviors and also outperforms existing ones.

We propose a Cooperative Opportunistic Automatic Repeat ReQuest (CoARQ) scheme to solve the HOL-blocking problem in infrastructure IEEE 802.11 WLANs. HOL blocking occurs when the head-of-the-line packet at the Access Point (AP) queue blocks the transmission of packets to other destinations resulting in severe throughput degradation. When the AP transmits a packet to a mobile station (STA), some of the nodes in the vicinity can overhear this packet transmission successfully. If the original transmission by the AP is unsuccessful, our CoARQ scheme chooses the station (STA or AP) with the best channel to the intended receiver as a relay and the chosen relay forwards the AP's packet to the receiver. This way, our scheme removes the bottleneck at the AP, thereby providing significant improvements in the throughput of the AP. We analyse the performance of our scheme in an infrastructure WLAN under a TCP controlled file download scenario and our analytical results are further validated by extensive simulations.

It is well known that the performance of the wireless communication systems can be enhanced by using multiple transmit and receive antennas, which is generally referred to as the MIMO technique, and has been incorporated into the IEEE 802.11n standard, i.e. one of the Wi-Fi systems. The MIMO technique has also been adopted by the 3GPP Long Term Evolution (LTE) and the 3GPP2 Ultra Mobile Broadband (UMB) standards. The space-time coding is a promising way to realize the gain in the wireless communications system using MIMO. The space time block code, and the orthogonal space time block code in particular have been proposed in research and implemented in practical wireless communication systems due to their low computational complexity in maximum likelihood decoding implementation. However, the code rates of the orthogonal space time block codes are usually lower than $3/4$ when the number of transmit antennas is greater than two, which limit their throughput. To increase the code rate and the throughput of the orthogonal space time block code for more than two transmit antennas, a family of new space-time block codes (STBC) for 3 and 4 transmit antennas in a MIMO wireless communication system have been proposed in this Ph.D. research. These new codes are orthogonal and achieve full diversity, full rate using Triple QPSK'' modulation, which is proposed in this research. We investigated the performance of these STBCs when the channel state information (CSI) is perfectly known at the receiver. The CSI is not known to the transmitter in all of the studies in this dissertation. An analytical bound of the probability of bit error is developed and the Monte Carlo simulation is used when investigating these new STBC codes. In practical wireless communication system, the CSI is generally not available at the receiver and it is usually estimated by the receiver through the pilot signals or training signals known to the receiver. No matter what channel estimation method is used, the estimate of CSI will not match the CSI exactly and is noisy. The performance of these new STBCs using theTriple QPSK'' modulation when the estimate of the CSI is employed to detect the symbol is investigated in this dissertation. An upper bound of the bit error probability is developed when the noisy CSI is used to detect the symbols. The performance of the new STBCs using the Triple QPSK'' modulation is also evaluated using Monte Carlo simulation. When the CSI is not available to either the receiver or the transmitter, the differential encoding and decoding algorithm is applied to these new STBCs, which use theTriple QPSK'' modulation. The results showed that these orthogonal STBCs achieve full diversity full rate using ""Triple-QPSK"" modulation with differential detection. This provides a means of achieving space diversity and multiplexing gain without the CSI. A new differential encoding and decoding algorithm is proposed and analyzed for STBCs with 3 transmit antennas, whose transmission matrix is not square matrix, as part of this Ph.D. research. The STBCs using this algorithm achieve full diversity the MIMO system can possibly provide.

This work evaluates the PAR performance in a MIMO OFDM-based WLAN system using the SLM approach. The investigated SLM scheme selects the transmitted sequence with the lowest average PAR over all transmitting antennas and retrieves the side information very accurately at the expense of a slight degradation of the PAR performance. The low probability of false side information can improve the overall detection performance of the MIMO-WLAN system with erroneous side information compared to the conventional SLM approaches, respectively.

次世代無線LAN IEEE802.11nシステムにおけるLDPCの性能に関する一検討

Automated interference detection is required for operation and management services in wireless networks as Wireless Local Area Networks (WLANs) based on IEEE 802.11 Standard since co-channel interference from other wireless transmitters occurs irregularly. We propose a new approach for detecting the presence of interference on 802.11 links. Our solution focuses on the Access Point (AP)-initiated monitoring approach without Wireless Station (STA)-initiated additional function and sniffer devices. Our approach uses the geographical distribution of the response delay of the Acknowledgment packet (ACK) to the downlink packet that AP transmitted to STAs. The proposed method consists of a continuous monitoring step and a periodical diagnosis step to measure network statistics by ACK response delay between an AP and STAs and to detect whether and where interference occurs respectively. Comprehensive simulation results show that the proposed approach has a good accuracy and low misdetection ratio for diagnosing the interference existence and location in IEEE 802.11 WLANs.

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