11 research outputs found

    A semi-blind channel estimation method for multiuser multiantenna OFDM systems

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    A subspace-based blind method is proposed for estimating the channel responses of a multiuser and multiantenna orthogonal frequency division multiplexing (OFDM) uplink system. It gives estimations to all channel responses subject to a scalar matrix ambiguity and does not need precise channel order information (only upper bound for the orders is required). Furthermore, the scalar ambiguity matrix can be easily resolved by using only one pilot OFDM block, given that the number of users is smaller than the number of symbols in the pilot symbol block. Equalization methods are discussed based on the estimated channels. By using partial knowledge of the channels, a multipath subspace method is proposed that reduces the computational complexity. Simulations show that the methods are effective and robust.published_or_final_versio

    Equalization of doubly selective channels using iterative and recursive methods

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    Novel iterative and recursive schemes for the equalization of time-varying frequency selective channels are proposed. Such doubly selective channels are shown to be common place in mobile communication systems, for example in second generation systems based on time division multiple access (TDMA) and so-called beyond third generation systems most probably utilizing orthogonal frequency division multiplexing (OFDM). A new maximum likelihood approach for the estimation of the complex multipath gains (MGs) and the real Doppler spreads (DSs) of a parametrically modelled doubly selective single input single output (SISO) channel is derived. Considerable complexity reduction is achieved by exploiting the statistical properties of the training sequence in a TDMA system. The Cramer-Rao lower bound for the resulting estimator is derived and simulation studies are employed to confirm the statistical efficiency of the scheme. A similar estimation scheme is derived for the MGs and DSs in the context of a multiple input multiple output (MIMO) TDMA system. A computationally efficient recursive equalization scheme for both a SISO and MIMO TDMA system which exploits the estimated MGs and DSs is derived on the basis of repeated application of the matrix inversion lemma. Bit error rate (BER) simulations confirm the advantage of this scheme over equalizers which have limited knowledge of such parameters. For OFDM transmission over a general random doubly selective SISO channel, the time selectivity is mitigated with an innovative relatively low complexity iterative method. Equalization is in effect split into two stages: one which exploits the sparsity in the associated channel convolution matrix and a second which performs a posteriori detection of the frequency domain symbols. These two procedures interact in an iterative manner, exchanging information between the time and frequency domains. Simulation studies show that the performance of the scheme approaches the matched filter bound when interleaving is also introduced to aid in decorrelation. Finally, to overcome the peak to average power problem in conventional OFDM transmission, the iterative approach is extended for single carrier with cyclic prefix (SCCP) systems. The resulting scheme has particularly low complexity and is shown by simulation to have robust performance.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

    Equalization of doubly selective channels using iterative and recursive methods

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    Novel iterative and recursive schemes for the equalization of time-varying frequency selective channels are proposed. Such doubly selective channels are shown to be common place in mobile communication systems, for example in second generation systems based on time division multiple access (TDMA) and so-called beyond third generation systems most probably utilizing orthogonal frequency division multiplexing (OFDM). A new maximum likelihood approach for the estimation of the complex multipath gains (MGs) and the real Doppler spreads (DSs) of a parametrically modelled doubly selective single input single output (SISO) channel is derived. Considerable complexity reduction is achieved by exploiting the statistical properties of the training sequence in a TDMA system. The Cramer-Rao lower bound for the resulting estimator is derived and simulation studies are employed to confirm the statistical efficiency of the scheme. A similar estimation scheme is derived for the MGs and DSs in the context of a multiple input multiple output (MIMO) TDMA system. A computationally efficient recursive equalization scheme for both a SISO and MIMO TDMA system which exploits the estimated MGs and DSs is derived on the basis of repeated application of the matrix inversion lemma. Bit error rate (BER) simulations confirm the advantage of this scheme over equalizers which have limited knowledge of such parameters. For OFDM transmission over a general random doubly selective SISO channel, the time selectivity is mitigated with an innovative relatively low complexity iterative method. Equalization is in effect split into two stages: one which exploits the sparsity in the associated channel convolution matrix and a second which performs a posteriori detection of the frequency domain symbols. These two procedures interact in an iterative manner, exchanging information between the time and frequency domains. Simulation studies show that the performance of the scheme approaches the matched filter bound when interleaving is also introduced to aid in decorrelation. Finally, to overcome the peak to average power problem in conventional OFDM transmission, the iterative approach is extended for single carrier with cyclic prefix (SCCP) systems. The resulting scheme has particularly low complexity and is shown by simulation to have robust performance

    Cooperative multiterminal radar and communication: a new paradigm for 6G mobile networks

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    The impending spectrum congestion imposed by the emergence of new bandwidth-thirsty applications may be mitigated by the integration of radar and classic communications functionalities in a common system. Furthermore, the merger of a sensing component into wireless communication networks has raised interest in recent years and it may become a compelling design objective for 6G. This article presents the evolution of the hitherto separate radar and communication systems towards their amalgam known as a joint radar and communication (RADCOM) system. Explicitly, we propose to integrate a radio sensing component into 6G. We consider an ultra-dense network (UDN) scenario relying on an active multistatic radar configuration and on cooperation between the access points across the entire coverage area. The technological trends required to reach a feasible integration, the applications anticipated and the open research challenges are identified, with an emphasis on high-accuracy network synchronization. The successful integration of these technologies would facilitate centimeter-level resolution, hence supporting compelling high-resolution applications for next-generation networks, such as robotic cars and industrial assembly lines.publishe

    Synchronization in CDMA systems

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    Ph.DDOCTOR OF PHILOSOPH

    Partial update blind adaptive channel shortening algorithms for wireline multicarrier systems

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    In wireline multicarrier systems a cyclic prefix is generally used to facilitate simple channel equalization at the receiver. The choice of the length of the cyclic prefix is a trade-off between maximizing the length of the channel for which inter-symbol interference is eliminated and optimizing the transmission efficiency. When the length of the channel is greater than the cyclic prefix, adaptive channel shorteners can be used to force the effective channel length of the combined channel and channel shortener to be within the cyclic prefix constraint. The focus of this thesis is the design of new blind adaptive time-domain channel shortening algorithms with good convergence properties and low computational complexity. An overview of the previous work in the field of supervised partial update adaptive filtering is given. The concept of property-restoral based blind channel shortening algorithms is then introduced together with the main techniques within this class of adaptive filters. Two new partial update blind (unsupervised) adaptive channel shortening algorithms are therefore introduced with robustness to impulsive noise commonly present in wireline multicarrier systems. Two further blind channel shortening algorithms are proposed in which the set of coefficients which is updated at each iteration of the algorithm is chosen deterministically. One of which, the partial up-date single lag autocorrelation maximization (PUSLAM) algorithm is particularly attractive due to its low computational complexity. The interaction between the receiver matched filter and the channel shortener is considered in the context of a multi-input single-output environment. To mitigate the possibility of ill-convergence with the PUSLAM algorithm an entirely new random PUSLAM (RPUSLAM) algorithm is proposed in which randomness is introduced both into the lag selection of the cost function underlying SLAM and the selection of the particular set of coefficients updated at each algorithm. This algorithm benefits from robust convergence properties whilst retaining relatively low computational complexity. All algorithms developed within the thesis are supported by evaluation on a set of eight carrier serving area test loop channels.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

    Transmit and receive techniques for MIMO-OFDM systems

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    Ph.DDOCTOR OF PHILOSOPH

    Transmitter Optimization in Multiuser Wireless Systems with Quality of Service Constraints

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    In this dissertation, transmitter adaptation for optimal resource allocation in wireless communication systems are investigated. First, a multiple access channel model is considered where many transmitters communicate with a single receiver. This scenario is a basic component of a. wireless network in which multiple users simultaneously access the resources of a wireless service provider. Adaptive algorithms for transmitter optimization to meet Quality-of-Service (QoS) requirements in a distributed manner are studied. Second, an interference channel model is considered where multiple interfering transmitter-receiver pairs co-exist such that a given transmitter communicates with its intended receiver in the presence of interference from other transmitters. This scenario models a wireless network in which several wireless service providers share the spectrum to offer their services by using dynamic spectrum access and cognitive radio (CR) technologies. The primary objective of dynamic spectrum access in the CR approach is to enable use of the frequency band dynamically and opportunistically without creating harmful interference to licensed incumbent users. Specifically, CR users are envisioned to be able to provide high bandwidth and efficient utilization of the spectrum via dynamic spectrum access in heterogeneous networks. In this scenario, a distributed method is investigated for combined precoder and power adaptation of CR transmitters for dynamic spectrum sharing in cognitive radio systems. Finally, the effect of limited feedback for transmitter optimization is analyzed where precoder adaptation uses the quantized version of interference information or the predictive vector quantization for incremental updates. The performance of the transmitter adaptation algorithms is also studied in the context of fading channels

    Joint channel estimation and data detection for multi-input multi-output single carrier cyclic-prefix (MIMO-SCCP) systems

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    10.1109/ICC.2008.117IEEE International Conference on Communications594-59
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