The IEEE 802.11 standard based wireless local area networks (WLANs) or Wi-Fi networks are critical to provide internet access in today’s world. The increasing demand for high data rate in Wi-Fi networks has led to several advancements in the 802.11 standard. Supporting MIMO transmissions with higher number of transmit antennas operating on wider bandwidths is one of the key capabilities for reaching higher throughput. However, the increase in sounding feedback overhead due to higher number of transmit antennas may significantly curb the throughput gain. In this paper, we develop an unsupervised learning-based method to reduce the sounding duration in a Wi-Fi MIMO link. Simulation results show that our method uses approximately only 8% of the number of bits required by the existing feedback mechanism and it can boost the system throughput by up to 52%.

The peak-to-average-power ratio (PAPR) of the frequency domain multiplexed wake-up signals (WUSs) specified in IEEE P802.11ba can be very large and difficult to manage since it depends on the number and allocation of the active channels, and the data rate on each channel. To address this issue, we propose a transmission scheme based on complementary sequences (CSs) for multiple WUSs multiplexed in the frequency domain. We discuss how to construct CSs compatible with the framework of IEEE P802.11ba by exploiting a recursive Golay complementary pair (GCP) construction to reduce the instantaneous power fluctuations in time. We compare the proposed scheme with the other options under a non-linear power amplifier (PA) distortion. Numerical results show that the proposed scheme can lower the PAPR of the transmitted signal in frequency division multiple access (FDMA) scenarios more than 3 dB and yields a superior error rate performance under severe PA distortion.

The IEEE 802.11 specification for Wireless Local Area Networks (WLANs) supports 20 MHz channels utilizing bandwidths up to 160 MHz. However, the support of devices simultaneously transmitting over different, non-overlapping channels, is not specifically addressed. Recently, there has been interest in developing a 802.11 specification for Carrier Grade Wi-Fi which has led to the requirement for solutions with efficient frequency resource utilization that are not currently supported. In this paper we propose a Medium Access Control (MAC) method, called Multi-User Parallel Channel Access (MU/PCA) that enables simultaneous transmission to multiple devices of various bandwidths, while maintaining backward compatibility with 802.11. We present analytical and simulation results demonstrating the throughput gains that can be achieved using the proposed MU/PCA scheme as compared to the current Carrier Sense Multiple Access/Collision Avoidance (CSMA/CA) scheme that is used in 802.11.

The IEEE 802.11 specification for Wi-Fi supports 20 MHz channels utilizing bandwidths up to 160 MHz. However, the support of devices simultaneously transmitting over different, non-overlapping channels, is not specifically addressed. Recently, there has been interest in developing an 802.11 specification for next generation Wi-Fi which has led to the requirement for solutions with efficient frequency resource utilization that are not currently supported. In this paper we continue the study of the Multi-User Parallel Channel Access (MU/PCA) scheme that enables simultaneous transmissions to multiple devices of various bandwidths, while maintaining backward compatibility with 802.11ac. We provide detailed physical layer design methods for MU/PCA, and propose several multi-user sub-channel selection algorithms. Finally we present numerical results which demonstrate the potential performance of the proposed MU/PCA algorithms.

In this paper we compare the implicit and explicit methods of providing channel state information (CSI) to the transmitter in a multi-user multiple-input-multiple-output (MU-MIMO) system as specified in the draft specification IEEE 802.11ac [1]. The comparison is made on the basis of both overhead requirements and packet-error-rate (PER) performance. We also propose a hybrid feedback scheme that combines the explicit and implicit feedback methods thus benefiting from more frequent calibration without incurring extra overhead.

We study methods to improve the performance of transmit beamforming as specified in the draft specification of IEEE 802.11ac [1]. Through numerical analysis of exemplary channel statistics, we propose methods to reduce overhead for Givens decomposition based explicit feedback. We further evaluate the channel estimation performance tradeoff using smoothing, and beamforming. Lastly we propose non-precoded channel estimation for low delay spread channels. Numerical performance of the proposed methods are also presented.

We propose a family of rate-compatible codes based on the concatenation of two linear codes with low-density generator matrix, which are a special class of LDPC codes with low encoding complexity. The proposed scheme is characterized by its simplicity of construction, and does not require optimization of the puncturing pattern.

We propose a modified algorithm for decoding of linear codes with low-density generator matrix (LDGM codes) over finite-state binary Markov channels. In order to avoid error floors, a serial concatenation of two LDGM codes is utilized. The hidden Markov model representing the channel is incorporated into the graph corresponding to the code, and the message passing algorithm is modified accordingly. The proposed scheme clearly outperforms systems in which the channel statistics are not exploited in the decoding process, allowing reliable communication at rates which are above the capacity of a memoryless channel with the same stationary bit error probability as the Markov channel. The proposed technique can be successfully applied for real wireless channels that can be modeled with hidden Markov models, such as indoor channels. In this case, the hidden Markov model representing the wireless channel can be estimated jointly with the decoding process

We introduce a layered scheme based on multilevel codes and random labeling of the MIMO constellation that attains constellation-constrained outage capacity in quasi-static fading channels. The proposed approach has the desirable features of using binary codes, not requiring demapper iterations and not applying constellation-expanding linear transformations in the complex field

We propose a modified algorithm for the decoding of linear codes with low-density generator matrix (LDGM) codes (a class of LDPC codes) over indoor and finite-state binary Markov channels. In order to avoid error floors, a concatenation of two LDGM codes is utilized. The hidden Markov model representing the channel is incorporated into the graph corresponding to the LDGM codes, and the message passing algorithm is modified accordingly. The proposed scheme clearly outperforms systems in which the channel statistics are not exploited in the decoding process, allowing reliable communication at rates which are above the capacity of a memoryless channel with the same stationary bit error probability as the Markov channel. Moreover, the proposed method can be successfully applied for real wireless channels that can be modeled with hidden Markov models, such as indoor channels.

We propose a modified algorithm for decoding of linear codes with low-density generator matrix (LDGM codes) over finite-state binary Markov channels. Simulation results show that the proposed scheme outperforms regular LDPC codes and achieves a performance close to that of turbo codes with much less encoding/decoding complexity

A system based on the use of systematic linear codes with low-density generator matrix (LDGM codes) for joint source-channel coding of multiterminal correlated binary sources is proposed. The encoding structure and different decoding possibilities are investigated and evaluated. For the case of binary sources and AWGN channels, the resulting performance is close to the theoretical limits.