Channel estimation and tracking algorithms for vehicle to vehicle communications

The vehicle-to-vehicle (V2V) communications channels are highly time-varying, making reliable communication difficult. This problem is particularly challenging because the standard of the V2V communications (IEEE 802.11p standard) is based on the WLAN IEEE 802.11a standard, which was designed for indoor, relatively stationary channels; so the IEEE 802.11p standard is not customized for outdo or, highly mobile non-stationary channels. In this thesis,We propose Channel estimation and tracking algorithms that are suitable for highly-time varying channels. The proposed algorithms utilize the finite alphabet property of the transmitted symbol, time domain truncation, decision-directed as well as pilot information. The proposed algorithm s improve the overall system performance in terms of bit error rates, enabling the system to achieve higher data rates and larger packet lengths at high relative velocities. Simulation results show that the proposed algorithms achieve improved performance for all the V2V channel models with different velocities, and for different modulation schemes and packet sizes as compared to the conventional least squares and other previously proposed channel estimation techniques for V2V channels

Spectrally Modulated Spectrally Encoded Framework Based Cognitive Radio in Mobile Environment

Radio spectrum has become a precious resource, and it has long been the dream of wireless communication engineers to maximize the utilization of the radio spectrum. Dynamic Spectrum Access (DSA) and Cognitive Radio (CR) have been considered promising to enhance the efficiency and utilization of the spectrum. Since some of the spectrum bands are occupied by primary users (PUs), the available spectrum for secondary users (SUs) are non-contiguous, and multi-carrier transmission technologies become the natural solution to occupy those non-contiguous bands. Non-contiguous multi-carrier based modulations, such as NC-OFDM (non-contiguous Orthogonal Frequency Division Multiplexing), NC-MC-CDMA (non-contiguous multi-carrier code division multiple access) and NC-SC-OFDM (non-contiguous single carrier OFDM), allow the SUs to utilize the available spectrum. Spectrally Modulated Spectrally Encoded (SMSE) framework offers a general framework to generate multi-carrier based waveform for CR. However, it is well known that all multi-carrier transmission technologies suffer significant performance degradation resulting from inter-carrier interference (ICI) in high mobility environments. Current research work in cognitive radio has not sufficiently considered and addressed this issue yet. Hence, it is highly desired to study the effect of mobility on CR communication systems and how to improve the performance through affordable low-complexity signal processing techniques. In this dissertation, we analyze the inter-carrier interference for SMSE based multi-carrier transmissions in CR, and propose multiple ICI mitigation techniques and carrier frequency offset (CFO) estimator. Specifically, (1) an ICI self-cancellation algorithm is adapted to the MC-CDMA system by designing new spreading codes to enable the system with the capability to reduce the ICI; (2) a blind ICI cancellation technique named Total ICI Cancellation is proposed to perfectly remove the ICI effect for OFDM and MC-CDMA systems and provide the performance approximately identical to that of the systems without ICI; (3) a novel modulation scheme, called Magnitude Keyed Modulation (MKM), is proposed to combine with SC-OFDM system and provide ICI immunity feature so that the system performance is not affected by the mobility or carrier frequency offset; (4) a blind carrier frequency offset estimation algorithm is proposed to accurately estimate the CFO; (5) finally, compared to traditional ICI analysis and cancellation techniques with assumption of constant carrier frequency offset among all the subcarriers, subcarrier varying CFO scenario is considered for the wideband multi-carrier transmission and non-contiguous multi-carrier transmission for CR, and an ICI total cancellation algorithm is proposed for the multi-carrier system with subcarrier varying CFOs to entirely remove the ICI

Spectrally Modulated Spectrally Encoded Framework Based Cognitive Radio in Mobile Environment

Radio spectrum has become a precious resource, and it has long been the dream of wireless communication engineers to maximize the utilization of the radio spectrum. Dynamic Spectrum Access (DSA) and Cognitive Radio (CR) have been considered promising to enhance the efficiency and utilization of the spectrum. Since some of the spectrum bands are occupied by primary users (PUs), the available spectrum for secondary users (SUs) are non-contiguous, and multi-carrier transmission technologies become the natural solution to occupy those non-contiguous bands. Non-contiguous multi-carrier based modulations, such as NC-OFDM (non-contiguous Orthogonal Frequency Division Multiplexing), NC-MC-CDMA (non-contiguous multi-carrier code division multiple access) and NC-SC-OFDM (non-contiguous single carrier OFDM), allow the SUs to utilize the available spectrum. Spectrally Modulated Spectrally Encoded (SMSE) framework offers a general framework to generate multi-carrier based waveform for CR. However, it is well known that all multi-carrier transmission technologies suffer significant performance degradation resulting from inter-carrier interference (ICI) in high mobility environments. Current research work in cognitive radio has not sufficiently considered and addressed this issue yet. Hence, it is highly desired to study the effect of mobility on CR communication systems and how to improve the performance through affordable low-complexity signal processing techniques. In this dissertation, we analyze the inter-carrier interference for SMSE based multi-carrier transmissions in CR, and propose multiple ICI mitigation techniques and carrier frequency offset (CFO) estimator. Specifically, (1) an ICI self-cancellation algorithm is adapted to the MC-CDMA system by designing new spreading codes to enable the system with the capability to reduce the ICI; (2) a blind ICI cancellation technique named Total ICI Cancellation is proposed to perfectly remove the ICI effect for OFDM and MC-CDMA systems and provide the performance approximately identical to that of the systems without ICI; (3) a novel modulation scheme, called Magnitude Keyed Modulation (MKM), is proposed to combine with SC-OFDM system and provide ICI immunity feature so that the system performance is not affected by the mobility or carrier frequency offset; (4) a blind carrier frequency offset estimation algorithm is proposed to accurately estimate the CFO; (5) finally, compared to traditional ICI analysis and cancellation techniques with assumption of constant carrier frequency offset among all the subcarriers, subcarrier varying CFO scenario is considered for the wideband multi-carrier transmission and non-contiguous multi-carrier transmission for CR, and an ICI total cancellation algorithm is proposed for the multi-carrier system with subcarrier varying CFOs to entirely remove the ICI

Iterative Joint Channel Estimation and Multi-User Detection for Multiple-Antenna Aided OFDM Systems

Multiple-Input-Multiple-Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) systems have recently attracted substantial research interest. However, compared to Single-Input-Single-Output (SISO) systems, channel estimation in the MIMO scenario becomes more challenging, owing to the increased number of independent transmitter-receiver links to be estimated. In the context of the Bell LAyered Space-Time architecture (BLAST) or Space Division Multiple Access (SDMA) multi-user MIMO OFDM systems, none of the known channel estimation techniques allows the number of users to be higher than the number of receiver antennas, which is often referred to as a “rank-deficient” scenario, owing to the constraint imposed by the rank of the MIMO channel matrix. Against this background, in this paper we propose a new Genetic Algorithm (GA) assisted iterative Joint Channel Estimation and Multi-User Detection (GA-JCEMUD) approach for multi-user MIMO SDMA-OFDM systems, which provides an effective solution to the multi-user MIMO channel estimation problem in the above-mentioned rank-deficient scenario. Furthermore, the GAs invoked in the data detection literature can only provide a hard-decision output for the Forward Error Correction (FEC) or channel decoder, which inevitably limits the system’s achievable performance. By contrast, our proposed GA is capable of providing “soft” outputs and hence it becomes capable of achieving an improved performance with the aid of FEC decoders. A range of simulation results are provided to demonstrate the superiority of the proposed scheme. Index Terms—Channel estimation, genetic algorithm, multiple-input-multiple-output, multi-user detection, orthogonal frequency division multiplexing, space division multiple access

Low Complexity Blind Equalization for OFDM Systems with General Constellations

This paper proposes a low-complexity algorithm for blind equalization of data in OFDM-based wireless systems with general constellations. The proposed algorithm is able to recover data even when the channel changes on a symbol-by-symbol basis, making it suitable for fast fading channels. The proposed algorithm does not require any statistical information of the channel and thus does not suffer from latency normally associated with blind methods. We also demonstrate how to reduce the complexity of the algorithm, which becomes especially low at high SNR. Specifically, we show that in the high SNR regime, the number of operations is of the order O(LN), where L is the cyclic prefix length and N is the total number of subcarriers. Simulation results confirm the favorable performance of our algorithm

Performance and Compensation of I/Q Imbalance in Differential STBC-OFDM

Differential space time block coding (STBC) achieves full spatial diversity and avoids channel estimation overhead. Over highly frequency-selective channels, STBC is integrated with orthogonal frequency division multiplexing (OFDM) to achieve high performance. However, low-cost implementation of differential STBC-OFDM using direct-conversion transceivers is sensitive to In-phase/Quadrature-phase imbalance (IQI). In this paper, we quantify the performance impact of IQI at the receiver front-end on differential STBC-OFDM systems and propose a compensation algorithm to mitigate its effect. The proposed receiver IQI compensation works in an adaptive decision-directed manner without using known pilots or training sequences, which reduces the rate loss due to training overhead. Our numerical results show that our proposed compensation algorithm can effectively mitigate receive IQI in differential STBC-OFDM.Comment: 7 pages, 2 figures, IEEE GLOBECOM 201

Iterative Joint Channel Estimation and Symbol Detection for Multi-User MIMO OFDM

Multiple-Input-Multiple-Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) systems have recently attracted substantial research interest. However, compared to Single-Input-Single-Output (SISO) systems, channel estimation in the MIMO scenario becomes more challenging, owing to the increased number of independent transmitter-receiver links to be estimated. In the context of the Bell LAyered Space-Time architecture (BLAST) or Space Division Multiple Access (SDMA) multi-user MIMO OFDM literature, no channel estimation technique allows the number of users to be higher than the number of receiver antennas, which is often referred to as an “overloaded” scenario. In this contribution we propose a new Genetic Algorithm (GA) assisted iterative joint channel estimation and multiuser detection approach for MIMO SDMA-OFDM systems, which exhibits a robust performance in the above-mentioned overloaded scenario. Furthermore, GA-aided Multi-User Detection (MUD) techniques found in the literature can only provide a hard-decision output, while the proposed GA is capable of providing “soft” outputs, hence achieving an improved performance with the aid of channel decoders. Finally, a range of simulation results are provided to demonstrate the superiority of the proposed scheme

A Summative Comparison of Blind Channel Estimation Techniques for Orthogonal Frequency Division Multiplexing Systems

The OFDM techniquei.e. Orthogonal frequency division multiplexing has become prominent in wireless communication since its instruction in 1950’s due to its feature of combating the multipath fading and other losses. In an OFDM system, a large number of orthogonal, overlapping, narrow band subchannels or subcarriers, transmitted in parallel, divide the available transmission bandwidth. The separation of the subcarriers is theoretically optimal such that there is a very compact spectral utilization. This paper reviewed the possible approaches for blind channel estimation in the light of the improved performance in terms of speed of convergence and complexity. There were various researches which adopted the ways for channel estimation for Blind, Semi Blind and trained channel estimators and detectors. Various ways of channel estimation such as Subspace, iteration based, LMSE or MSE based (using statistical methods), SDR, Maximum likelihood approach, cyclostationarity, Redundancy and Cyclic prefix based. The paper reviewed all the above approaches in order to summarize the outcomes of approaches aimed at optimum performance for channel estimation in OFDM system

Scattered Pilots and Virtual Carriers Based Frequency Offset Tracking for OFDM Systems: Algorithms, Identifiability, and Performance Analysis

In this paper, we propose a novel carrier frequency offset (CFO) tracking algorithm for orthogonal frequency division multiplexing (OFDM) systems by exploiting scattered pilot carriers and virtual carriers embedded in the existing OFDM standards. Assuming that the channel remains constant during two consecutive OFDM blocks and perfect timing, a CFO tracking algorithm is proposed using the limited number of pilot carriers in each OFDM block. Identifiability of this pilot based algorithm is fully discussed under the noise free environment, and a constellation rotation strategy is proposed to eliminate the c-ambiguity for arbitrary constellations. A weighted algorithm is then proposed by considering both scattered pilots and virtual carriers. We find that, the pilots increase the performance accuracy of the algorithm, while the virtual carriers reduce the chance of CFO outlier. Therefore, the proposed tracking algorithm is able to achieve full range CFO estimation, can be used before channel estimation, and could provide improved performance compared to existing algorithms. The asymptotic mean square error (MSE) of the proposed algorithm is derived and simulation results agree with the theoretical analysis