Uplink Orthogonal Frequency Division Multiple Access Research Articles

Efficient Space-Time Signal Processing Scheme of Frequency Synchronization and Positioning for Sensor Networks.

The orthogonal frequency division multiple access (OFDMA) technique has been widely employed in sensor networks as the data modulation scheme. This study presents a one-dimensional (1D) space-time signal processing scheme for the joint estimation of direction of arrival (DOA) and carrier frequency offsets (CFOs) in OFDMA uplink systems. The proposed approach, initiated by a one-dimensional ESPRIT algorithm, involves estimating the DOAs of the received signal to identify subscriber positions. Spatial beamformers are then used to suppress multiple access interference and separate each subscriber's signal from the received signal. The outputs of the spatial beamformer are decimated to estimate the CFO of each subscriber. Compared with conventional two-dimensional parameter estimation algorithms, the proposed one-dimensional algorithm has a higher estimation accuracy and significantly lower computational complexity.

CFX: Contention-Free Channel Access for IEEE 802.11ax

Orthogonal frequency-division multiple access (OFDMA) has attracted great attention as a key technology for uplink enhancement for Wi-Fi, since it can effectively reduce network congestion and channel access delay. Unfortunately, the traditional random access protocol of Wi-Fi seldom allows these benefits to be achieved, especially in dense network environments, as the access point (AP) rarely gains the channel access needed to trigger OFDMA uplink transmissions due to severe frame collisions. To address this problem, we propose a new channel access scheme called Contention-Free Channel Access for 802.11ax (CFX). In the proposed scheme, users can access the channel without contention, since they are guaranteed a transmission opportunity immediately after another user's transmission. To realize CFX on top of the existing Buffer Status Report/BSR Poll (BSR/BSRP) exchange protocol of 802.11ax, we develop an additional scheme based on shared channel access that helps the AP to obtain the buffer status of users and manage a contention-free channel access schedule. In addition, in order to appropriately utilize the savings from the reduced frame collisions, we conduct sum throughput maximization using an actor-critic proximal policy optimization (PPO)-based deep reinforcement learning approach. The results of an extensive evaluation show that CFX not only significantly improves the uplink performance of Wi-Fi in terms of throughput and channel access delay but can also dynamically adjust the parameters in response to changes in the network status.

Resource Allocation and Beamforming Optimization for IRS-Assisted OFDMA Uplink in C-RAN

This letter studies the resource allocation and passive beamforming for the cloud radio access network (C-RAN) with orthogonal frequency division multiple access (OFDMA) assisted by intelligent reflecting surface (IRS). Specifically, we consider the uplink transmission where remote radio heads (RRHs) quantize the received signals from the users by independent point-to-point compression and transmit the quantization bits to the baseband unit (BBU) pool through capacity-limited fronthaul links. We jointly optimize the resource allocation and passive beamforming to maximize the uplink sum-rate, using alternating approach and successive convex approximation (SCA) technique. Numerical results verify the performance gain brought by IRS and validate the effectiveness of the proposed algorithm.

Preparing Wi-Fi 7 for Healthcare Internet-of-Things.

The healthcare Internet of Things (H-IoT) is an interconnection of devices capable of sensing and transmitting information that conveys the status of an individual’s health. The continuous monitoring of an individual’s health for disease diagnosis and early detection is an important application of H-IoT. Ambient assisted living (AAL) entails monitoring a patient’s health to ensure their well-being. However, ensuring a limit on transmission delays is an essential requirement of such monitoring systems. The uplink (UL) transmission during the orthogonal frequency division multiple access (OFDMA) in the wireless local area networks (WLANs) can incur a delay which may not be acceptable for delay-sensitive applications such as H-IoT due to their random nature. Therefore, we propose a UL OFDMA scheduler for the next Wireless Fidelity (Wi-Fi) standard, the IEEE 802.11be, that is compliant with the latency requirements for healthcare applications. The scheduler allocates the channel resources for UL transmission taking into consideration the traffic class or access category. The results demonstrate that the proposed scheduler can achieve the required latency for H-IoT applications. Additionally, the performance in terms of fairness and throughput is also superior to state-of-the-art schedulers.

Will OFDMA Improve the Performance of 802.11 Wifi Networks?

WiFi 6 based on the IEEE 802.11ax amendment is intended to improve spectral efficiency and area throughput operations in high density environments. This is achieved (among other methods) by the introduction of Orthogonal Frequency Division Multiple Access (OFDMA) and enhanced multi-user Multiple Input Multiple Output (MU-MIMO) features. In this work, we explore the performance of downlink and uplink OFDMA in 802.11ax via extensive simulation based evaluation (latency, throughput, range) compared to conventional single user (SU) transmissions. Based on our results, we conclude that OFDMA can reduce the median latency from ~5 ms to less than 1 ms in non-saturation conditions. When used in conjunction with efficient multi-user buffer status report and restricted EDCA mechanisms, OFDMA can increase the saturation throughput by more than 10 percent. Moreover, UL OFDMA also improves aggregate throughput at longer ranges due to the narrower sub-channels (equivalently increased transmit power spectral density); four stations achieve an aggregate throughput 35 percent higher than a station transmitting SU frames and located at a range 1.5 times closer to the access point.

Utility optimization of grouping-based uplink OFDMA random access for the next generation WLANs

In this paper, a grouping-based uplink orthogonal frequency division multiple access (OFDMA) random access method is studied which can improve users’ satisfaction in the next generation wireless local area networks (WLANs). The next generation WLANs standard, IEEE 802.11ax introduces a random access mechanism, uplink OFDMA random access (UORA), to allow users to access channel randomly. Although UORA has the advantages of low signaling overhead, no need to report uplink transmission requirements, it does not have any characteristics to improve users’ satisfaction. Because the AP can’t allocate resources to users adopting UORA, some users’ quality of experience (QoE) will decline greatly. In this paper, a grouping-based UORA (G-UORA) method is proposed. The AP determines the number of groups, and then clusters users to different groups according to their utility. Then, the AP assigns resources to these groups to maximize the total utility of all users. We present a theoretical utility prediction model of G-UORA and propose the corresponding resource allocation algorithm based on utility. According to simulation results, the algorithm achieves better users’ satisfaction and fairness than the traditional UORA mechanism in IEEE 802.11ax and the user utility gain is 1.6 times. Therefore, the proposed method has greater practical significance.

Performance evaluation of OFDMA and MU-MIMO in 802.11ax networks

IEEE 802.11ax defines a new access method called Orthogonal Frequency Division Multiple Access (OFDMA) which can be used in both downlink (DL) and uplink (UL) directions. OFDMA divides the bandwidth into several Resource Units (RUs) and allows multiple stations to transmit or to receive simultaneously. UL OFDMA supports Scheduled Access (SA) RUs and Random Access (RA) RUs. Only scheduled stations are allowed to send on SA RUs, while the other stations should contend for the RA RUs. Moreover, 802.11ax defines UL MU-MIMO and enhances DL MU-MIMO. In this paper, we introduce and evaluate the efficiency of DL and UL multi-user transmissions using OFDMA and MIMO. Our results show that UL OFDMA is particularly useful when multiple stations regularly need to transmit few MPDUs. In this case, UL OFDMA may outperform full bandwidth access with up to 400%. Moreover, we find that increasing the number of RA RUs does not effectively reduce the collision rate but significantly decreases the throughput. Furthermore, we show that UL MU-MIMO significantly improves the network throughput and that the performance of DL MU-MIMO is clearly enhanced thanks to the decreased duration of the channel sounding procedure.

A low complexity iterative equalization technique for OFDMA and SC-FDMA uplink systems with Tx-Rx IQ imbalance and CFO under doubly selective channels

The next-generation wireless communication systems must address the compensation of in-phase and quadrature phase imbalance (IQI), carrier frequency offset (CFO), and doubly selective channel (DSC) to provide a high quality of service for high mobility users with low-cost radio . None of the existing works consider all these RF impairments under DSC for multi-user scenario. To address this gap, in this paper, we propose an iterative equalization technique to compensate the multi-user interference (MUI) and self inter-carrier interference (S-ICI) induced by the joint effect of transmitter IQI, receiver IQI, CFO and DSC for single carrier frequency division multiple access (SC-FDMA) and orthogonal frequency division multiple access (OFDMA) uplink systems. In each iteration of the proposed equalization technique, the extrinsic information from the decoder is used to cancel the MUI and S-ICI from the received signal. After interference cancellation, each mirror subcarriers pairs are equalized simultaneously. Additionally, unlike existing works, our proposed technique does not put any restriction on the carrier assignment scheme (CAS) used with OFDMA/SC-FDMA systems. Further, to validate the performance of the proposed compensation scheme analytically, we derive an upper bound on the bit error rate (BER) of coded OFDMA and SC-FDMA system without MUI and S-ICI. It is established that the system BER with the proposed technique satisfies the derived upper bound as the iteration converges, demonstrating the effective cancellation of MUI and S-ICI due to all the impairments.

Hybrid OFDMA Random Access With Resource Unit Sensing for Next-Gen 802.11ax WLANs

IEEE 802.11ax partitions a regular 20MHz channel into smaller sub-channels called resource units to support simultaneous multiuser operation using orthogonal frequency division multiple access (OFDMA). Uplink OFDMA random access (UORA) in IEEE 802.11ax allows stations to transmit via a scheduled random access mechanism. UORA is initiated via a trigger frame which aside from serving as a synchronization mechanism, also informs stations which resource units are allowed for random access. Using the trigger frame information, the stations engage in an OFDMA backoff process to win access to a resource unit. Similar to slotted ALOHA, the maximum normalized throughput of UORA is only 37 percent due to high probability of collisions at high loads. To reduce collisions, we equip UORA with carrier sensing capability resulting in a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">new</i> uplink hybrid UORA (H-UORA) OFDMA access mechanism. Unlike other multi-carrier CSMA methods previously proposed in literature, H-UORA is an easily implementable modification to current 802.11ax WLANs. We show that H-UORA can achieve a normalized throughput of at least 80 percent (which increases further depending on the buffering capabilities of the access point) using various numerical analysis and simulations.

MU-MIMO enabled uplink OFDMA MAC protocol in dense IEEE 802.11ax WLANs

IEEE 802.11ax supports orthogonal frequency division multiple access (OFDMA) for uplink (UL) transmissions where stations (STAs) access randomly chosen resource units (RUs) in a distributed manner. Nevertheless, as the number of STAs increases, frequent collisions can occur, which lead to throughput degradation in UL transmissions. To address this problem, we propose a multi-user multiple-input multiple-output (MU-MIMO) enabled UL OFDMA random access (MORA) protocol. MORA combines the ideas of OFDMA and MU-MIMO, and thus more than one STA can share the same RU, which can significantly reduce the collision probability in congested situations. Analytical and simulation results demonstrate that MORA improves the throughput of the standard OFDMA-only protocol significantly.

Multi-Dimensional Busy-Tone Arbitration for OFDMA Random Access in IEEE 802.11ax

IEEE 802.11ax has adopted orthogonal frequency division multiple access (OFDMA) to support multi-user (MU) transmissions. There exist two uplink MU OFDMA access methods in IEEE 802.11ax. The first one is uplink OFDMA random access (UORA) in which stations randomly select resource units (RUs) to send physical protocol data units (PPDUs), so its access efficiency is low. The second one is uplink OFDMA nonrandom access (UONRA) in which the access point (AP) schedules MU transmissions based on buffer status reports (BSR) from stations. However, stations usually rely on UORA to send BSRs, so the low efficiency of UORA can be a bottleneck of UONRA. Thus, UORA needs to be renovated to improve the performance of itself and UONRA. To this end, a multi-dimensional busy-tone arbitration (MBTA) mechanism is developed in this paper to reduce collisions among stations contending the same RU. Since there lacks an algorithm in IEEE 802.11ax to support coexistence of UORA and UONRA, a dynamic access-method selection (DAMS) algorithm is designed for the AP and stations to choose an optimal access method. Both MBTA and DAMS are analyzed rigorously and are further validated via simulations. The analytical and simulation results show that: 1) The MBTA dramatically improves the access efficiency of UORA; 2) DAMS always achieves a higher throughput than both UORA and UONRA.

Group-Based Uplink OFDMA Random Access Algorithm for Next-Generation WLANs

The traditional wireless local area network(WLAN) standard, IEEE 802.11, adopts carrier sense multiple access/collision avoidance(CSMA/CA) mechanism to allow a single user to compete for channel access. The upcoming WLAN standard, IEEE 802.11ax, combines orthogonal frequency division multiple access(OFDMA) technology with random access, and use Uplink OFDMA Random Access(UORA) technology as uplink random access. Therefore, UORA which allow multiple users to access channel at the same time can improve the utilization of network resources. Although UORA technology in IEEE 802.11ax has the advantage of low signaling overhead, when the number of users of network is large, the increase of random access collisions will lead to the decrease of network throughput. Therefore, we propose a group-based UORA method. As a central scheduling node, Access Point(AP) divide Stations(STAs) and resources to groups and sets different GroupID for different groups. STAs can only access resources with the same GroupID randomly. The validity of group-based UORA method is verified by mathematical model analysis and simulation. The network throughput of our group-based UORA is higher than that of the original UORA in IEEE 802.11ax, so it has great practical significance.

Joint rate adaptation and resource allocation for real-time H.265/HEVC video transmission over uplink OFDMA systems

We consider multiuser video communication over uplink orthogonal frequency-division multiple access (OFDMA) systems. A cross-layer algorithm of joint bit allocation, packet scheduling and wireless resource assignment are proposed to minimize the end-to-end expected video distortion. Video rate adaptation is performed under the wireless resource constraints. The target number of encoding bits for each video packet is obtained to minimize the estimated distortion based on the online content-based rate-distortion function. Due to the inaccuracy of the rate control algorithm in H.265/HEVC encoding, the actual number of bits may differ from the target. Accordingly, the actual encoder distortion may deviate from the estimated distortion. Then, we propose an iterative algorithm to re-assign wireless resources based on the actual number of encoded bits to obtain the final resource allocation policy and packet scheduling decision. Numerical simulation results show that our proposed approach significantly outperforms the baseline algorithms in terms of received video quality.

Sparse Bayesian Learning Assisted CFO Estimation Using Nonnegative Laplace Priors

This correspondence paper aims at addressing the estimation of carrier frequency offset (CFO) for the uplink orthogonal frequency-division multiple access systems. Since the CFOs of the signals from different active users are sparsely distributed in the frequency domain, a sparse Bayesian learning (SBL) is tailored to determine the CFO in this paper, ending up with the SBL assisted CFO (SBL-CFO) estimator. In particular, the CFO estimation problem is first formulated as a sparse nonnegative least squares (S-NNLS) problem. Meanwhile, background noise and sampling errors are mitigated utilizing a selection matrix and a whitening filter, respectively. This enables us to exploit the SBL with nonnegative Laplace prior (SBL-NLP) to solve the S-NNLS problem. Furthermore, in order to make the convergence of the SBL-NLP algorithm faster and its estimation more accurate, the hyperprior inherent in the SBL-NLP algorithm is initialized by the traditional SBL with nonnegative Gaussian prior. Simulation results show that our proposed SBL-CFO estimator significantly outperforms the state-of-the-art estimators in terms of estimation accuracy, especially when the CFOs and the number of active users are large.

Solving IQ Mismatch Problem for Two-Path Successive Relaying OFDMA Uplink Systems With Direct Conversion Transceivers

In this letter, the properties of two-path successive relaying systems are exploited to develop an iterative decision directed algorithm to estimate in-phase/quadrature-phase mismatch parameters occurring at the transmitters, relays, and destination for the uplink orthogonal frequency-division multiple access transmission. These parameters along with the actual channel taps of different links are treated as a single unknown parameter to be estimated. A space-alternating generalized expectation-maximization tool is employed to compute the maximum-likelihood estimate. The proposed algorithm iterates between data detector and estimator in order to refine the estimation process. Simulation results confirm the effectiveness of the proposed estimator.

Using OFDMA for MU-MIMO User Selection in 802.11ax-Based Wi-Fi Networks

Two innovative multi-user (MU) communication mechanisms, multi-user multi-input multi-output (MU-MIMO) and orthogonal frequency division multiple access (OFDMA), have recently attracted much attention as key technologies to boost the capabilities of 802.11 Wi-Fi systems. The method of MU transmission in Wi-Fi systems still suffers from severe problems with channel state information (CSI) feedback overhead, however, and this precludes obtaining much higher MU-MIMO gains through user selection. Although in 802.11ax-based Wi-Fi systems the methods used for uplink OFDMA transmission and downlink MU-MIMO transmission bear a great deal of resemblance to each other, in the sense that both are initiated by the AP, this similarity in protocol is not appropriately utilized for close collaboration between the two technologies. This paper proposes MUSE, a novel multi-user transmission scheme for 802.11ax networks. By exploiting uplink OFDMA transmissions for MU-MIMO user selection, MUSE takes advantage of both OFDMA and MU-MIMO functionalities. In particular, the AP estimates and gathers multiple CSI values from the uplink OFDMA frame, and this channel information is then used to find the optimal downlink MU-MIMO receiver group to maximize the system utility. To realize MUSE, a new OFDMA resource allocation algorithm and frame structure are developed. Extensive MATLAB simulation results show that MUSE significantly improves the network throughput, even in dense network scenarios, and also works effectively in co-existence with legacy nodes.

Concept and Analysis of Capacity Entropy for Uplink Multi-User Media Access Control for the Next-Generation WLANs

IEEE 802.11ax, an emerging standard for the next-generation wireless local area networks (WLANs), pursues to improve network throughput in high-density deployment scenarios by introducing high-efficiency mechanisms into both media access control (MAC) layer and physical (PHY) layer. In IEEE 802.11ax, high-efficiency multi-user media access control (MU-MAC) is adopted for both uplink and downlink access mechanisms. As for the uplink MU-MAC, it can be further subdivided into two categories, uplink orthogonal frequency division multiple access (OFDMA) scheduling access (UOSA) and uplink OFDMA random access (UORA). How to effectively measure and optimize the joint carrying capacity (JCC) of the networks where both scheduling access mode and random access mode are supported is a key problem for the design of the uplink access mechanism of the 802.11ax. Firstly, in this paper, the concept of capacity entropy for multi-user access (CEM) is proposed to quantitatively measure the JCC of the networks. Secondly, the UORA is modeled and analyzed and we get the access probability of UORA (PUORA) by using an enhanced Markov chain, then we can calculate the capacity entropy of UORA. Based on it, the CEM of the 802.11ax is further analyzed. Finally, based on the adopted MU-MAC framework in 802.11ax standard draft, an efficient hybrid access strategy (HAS) is proposed, which combines a greedy scheduling strategy based on capacity constraints and a method based on channel quality perception of stations (STAs) in UORA. Simulation results show that HAS achieves higher CEM. In summary, it is believed that the proposed concept of CEM will pave a new technical way to investigate problems of how to optimize the JCC for the next-generation WLANs.

Partial Transmit Sequence Scheme for Envelope Fluctuation Reduction in OFDMA Uplink Systems

This letter proposes a new partial transmit sequence (PTS) scheme to reduce envelope fluctuations in orthogonal frequency-division multiple access (OFDMA) uplink systems. We found that the conventional PTS can be seriously degraded in the non-contiguous allocation of OFDMA uplink systems due to the linearity in the conventional phase rotations. To overcome this problem, we propose a new phase rotation using the complex conjugate, which can be implemented without multiplication like the conventional phase rotations. Simulation results show that the proposed PTS outperforms the conventional PTS in terms of cubic metric and bit error rate.

Blind CFO Estimation in OFDMA Uplink Transmission With General Carrier Assignment Scheme

Carrier frequency offset (CFO) estimation is a challenging issue in uplink orthogonal frequency division multiple access (OFDMA) systems. Most existing blind estimation methods for these systems are derived under certain types of carrier assignment scheme (CAS). In this letter, we propose a new blind CFO estimation algorithm for uplink OFDMA systems with constant modulus constellation. The proposed estimator can estimate CFO under any type of CAS, with only one antenna at the receiver. Moreover, the proposed method can be applied to OFDMA with or without virtual/null subcarriers. Simulation results show that the proposed estimator performs well under arbitrary CAS.

Carrier Frequency Offset Estimation in Uplink OFDMA Systems: An Approach Relying on Sparse Recovery

This paper proposes a novel blind carrier frequency offset (CFO) estimator, namely the sparse recovery assisted CFO (SR-CFO) estimator, for the uplink orthogonal frequency-division multiple access (OFDMA) systems. By exploiting the sparsity embedded in the OFDMA data, the CFO estimation is formulated as an optimization problem of sparse recovery with high-resolution. Meanwhile, in order to enhance the estimation accuracy of CFOs, background noise and sampling errors are mitigated by exploiting the structure of the noise covariances matrix in the transformed observation data, and the asymptotic distribution of the sampling errors. Furthermore, we propose an approach for deriving the regularization parameter used by the SR-CFO estimator, so as to control the tradeoff between the data fitting error and the sparsity of solution. The performance of the proposed SR-CFO estimator along with other four existing estimators is investigated and compared. Numerical results show that the proposed SR-CFO estimator is superior to the state-of-the-art estimators in terms of the estimation reliability.