MIMO Transmission with Residual Transmit-RF Impairments

Physical transceiver implementations for multiple-input multiple-output (MIMO) wireless communication systems suffer from transmit-RF (Tx-RF) impairments. In this paper, we study the effect on channel capacity and error-rate performance of residual Tx-RF impairments that defy proper compensation. In particular, we demonstrate that such residual distortions severely degrade the performance of (near-)optimum MIMO detection algorithms. To mitigate this performance loss, we propose an efficient algorithm, which is based on an i.i.d. Gaussian model for the distortion caused by these impairments. In order to validate this model, we provide measurement results based on a 4-stream Tx-RF chain implementation for MIMO orthogonal frequency-division multiplexing (OFDM).Comment: to be presented at the International ITG Workshop on Smart Antennas - WSA 201

Channel, Phase Noise, and Frequency Offset in OFDM Systems: Joint Estimation, Data Detection, and Hybrid Cramer-Rao Lower Bound

Oscillator phase noise (PHN) and carrier frequency offset (CFO) can adversely impact the performance of orthogonal frequency division multiplexing (OFDM) systems, since they can result in inter carrier interference and rotation of the signal constellation. In this paper, we propose an expectation conditional maximization (ECM) based algorithm for joint estimation of channel, PHN, and CFO in OFDM systems. We present the signal model for the estimation problem and derive the hybrid Cramer-Rao lower bound (HCRB) for the joint estimation problem. Next, we propose an iterative receiver based on an extended Kalman filter for joint data detection and PHN tracking. Numerical results show that, compared to existing algorithms, the performance of the proposed ECM-based estimator is closer to the derived HCRB and outperforms the existing estimation algorithms at moderate-to-high signal-to-noise ratio (SNR). In addition, the combined estimation algorithm and iterative receiver are more computationally efficient than existing algorithms and result in improved average uncoded and coded bit error rate (BER) performance

Improving performance of pedestrian positioning by using vehicular communication signals

Pedestrian-to-vehicle communications, where pedestrian devices transmit their position information to nearby vehicles to indicate their presence, help to reduce pedestrian accidents. Satellite-based systems are widely used for pedestrian positioning, but have much degraded performance in urban canyon, where satellite signals are often obstructed by roadside buildings. In this paper, we propose a pedestrian positioning method, which leverages vehicular communication signals and uses vehicles as anchors. The performance of pedestrian positioning is improved from three aspects: (i) Channel state information instead of RSSI is used to estimate pedestrian-vehicle distance with higher precision. (ii) Only signals with line-of-sight path are used, and the property of distance error is considered. (iii) Fast mobility of vehicles is used to get diverse measurements, and Kalman filter is applied to smooth positioning results. Extensive evaluations, via trace-based simulation, confirm that (i) Fixing rate of positions can be much improved. (ii) Horizontal positioning error can be greatly reduced, nearly by one order compared with off-the-shelf receivers, by almost half compared with RSSI-based method, and can be reduced further to about 80cm when vehicle transmission period is 100ms and Kalman filter is applied. Generally, positioning performance increases with the number of available vehicles and their transmission frequency

Partial OFDM Symbol Recovery to Improve Interfering Wireless Networks Operation in Collision Environments

The uplink data rate region for interfering transmissions in wireless networks has been characterised and proven, yet its underlying model assumes a complete temporal overlap. Practical unplanned networks, however, adopt packetized transmissions and eschew tight inter-network coordination, resulting in packet collisions that often partially overlap, but rarely ever completely overlap. In this work, we report a new design called (), that specifically targets the parts of data symbols that experience no interference during a packet collision. bootstraps a successive interference cancellation (SIC) like decoder from these strong signals, thus improving performance over techniques oblivious to such partial packet overlaps. We have implemented on the WARP software-defined radio platform and in trace-based simulation. Our performance evaluation presents experimental results from this implementation operating in a 12node software network testbed, spread over two rooms in a nonlineofsight indoor office environment. Experimental results confirm that our proposal decoder is capable of decoding up to 60 % of collided frames depending on the type of data and modulation used. This consistently leads to throughput enhancement over conventional WiFi under different scenarios and for the various data types tested, namely downlink bulk TCP, downlink videoondemand, and uplink UDP

Multi-Relay Communications in the Presence of Phase Noise and Carrier Frequency Offsets

Impairments like time varying phase noise (PHN) and carrier frequency offset (CFO) result in loss of synchronization and poor performance of multi-relay communication systems. Joint estimation of these impairments is necessary in order to correctly decode the received signal at the destination. In this paper, we address spectrally-efficient multi-relay transmission scenarios where all the relays simultaneously communicate with the destination. We propose an iterative pilot-aided algorithm based on the expectation conditional maximization (ECM) for joint estimation of multipath channels, Wiener PHNs, and CFOs in decode-and-forward (DF) based multi-relay orthogonal frequency division multiplexing (OFDM) systems. Next, a new expression of the hybrid Cramér-Rao lower bound (HCRB) for the multi-parameter estimation problem is derived. Finally, an iterative receiver based on an extended Kalman filter (EKF) for joint data detection and PHN tracking is employed. Numerical results show that the proposed estimator outperforms existing algorithms and its mean square error performance is close to the derived HCRB at differnt signal-to-noise ratios (SNRs) for different PHN variances. In addition, the combined estimation algorithm and iterative receiver can significantly improve average bit-error rate (BER) performance compared to existing algorithms. In addition, the BER performance of the proposed system is close to the ideal case of perfect channel impulse responses (CIRs), PHNs and CFOs estimation

On relaxing constraints on multi-branch RF front-end for a SIMO OFDM receiver – A global system evaluation scheme

International audienceIn this article, main of the presented results are obtained by taking into account most as possible realistic working condition by the use of a global system evaluation scheme based on Agilent Technologies equipments. As presented in previous works, realistic consideration of the characteristics of transmission channel, the antenna coupling and also the channel correlation would indeed allow a fast and effective design of multiantenna wireless systems in order to obtain an important design cycle reducing. The first part presents the used global system level approach and the associated tools with some theoretical, simulated and measured results in order to validate the developed testbed radio plateform. In the second part, the three presented RF impairments are considered one by one in a Zero-IF down conversion structure and their effect on OFDM transmission performances are detailed. In the last part, after a short description of the SIMO processing that is used, the natural compensation of each RF impairment it is possible to obtained taking advantage of space diversity is presented. Results given in this part are obtained by taking into account different measured propagation channels (AWGN or fading channels) and a complete 802.11g structure

Practical interference mitigation for Wi-Fi systems

Wi-Fi's popularity is also its Achilles' heel since in the dense deployments of multiple Wi-Fi networks typical in urban environments, concurrent transmissions interfere. The advent of networked devices with multiple antennas allows new ways to improve Wi-Fi's performance: a host can align the phases of the signals either received at or transmitted from its antennas so as to either maximize the power of the signal of interest through beamforming or minimize the power of interference through nulling. Theory predicts that these techniques should enable concurrent transmissions by proximal sender-receiver pairs, thus improving capacity. Yet practical challenges remain. Hardware platform limitations can prevent precise measurement of the wireless channel, or limit the accuracy of beamforming and nulling. The interaction between nulling and Wi-Fi's OFDM modulation, which transmits tranches of a packet's bits on distinct subcarriers, is subtle and can sacrifice the capacity gain expected from nulling. And in deployments where Wi-Fi networks are independently administered, APs must efficiently share channel measurements and coordinate their transmissions to null effectively. In this thesis, I design and experimentally evaluate beamforming and nulling techniques for use in Wi-Fi networks that address the aforementioned practical challenges. My contributions include: - Cone of Silence (CoS): a system that allows a Wi-Fi AP equipped with a phased-array antenna but only a single 802.11g radio to mitigate interference from senders other than its intended one, thus boosting throughput; - Cooperative Power Allocation (COPA): a system that efficiently shares channel measurements and coordinates transmissions between independent APs, and cooperatively allocates power so as to render received power across OFDM subcarriers flat at each AP's receiver, thus boosting throughput; - Power Allocation for Distributed MIMO (PADM): a system that leverages intelligent power allocation to mitigate inter-stream interference in distributed MIMO wireless networks, thus boosting throughput

Full-Duplex Systems Using Multi-Reconfigurable Antennas

Full-duplex systems are expected to achieve 100% rate improvement over half-duplex systems if the self-interference signal can be significantly mitigated. In this paper, we propose the first full-duplex system utilizing Multi-Reconfigurable Antenna (MRA) with ?90% rate improvement compared to half-duplex systems. MRA is a dynamically reconfigurable antenna structure, that is capable of changing its properties according to certain input configurations. A comprehensive experimental analysis is conducted to characterize the system performance in typical indoor environments. The experiments are performed using a fabricated MRA that has 4096 configurable radiation patterns. The achieved MRA-based passive self-interference suppression is investigated, with detailed analysis for the MRA training overhead. In addition, a heuristic-based approach is proposed to reduce the MRA training overhead. The results show that at 1% training overhead, a total of 95dB self-interference cancellation is achieved in typical indoor environments. The 95dB self-interference cancellation is experimentally shown to be sufficient for 90% full-duplex rate improvement compared to half-duplex systems.Comment: Submitted to IEEE Transactions on Wireless Communication