Abstract-Multiple symbol differential detection (MSDD) offers high-performance symbol recovery and bypasses training or channel estimation, which are highly desired features in lowpower ultra-wideband (UWB) communications. However, UWB impulse radios entail distinct signaling structures and stringent performance-complexity requirements, giving rise to the need for a new MSDD scheme capable of coping with dense multipath UWB channels and detecting a large block of symbols at practical complexity. To this end, this paper develops a novel MSDD-based UWB receiver that attains the desired performance advantages by jointly detecting blocks of received symbols based on the autocorrelation principle. To enable practical implementations at desired performance versus complexity tradeoffs, new optimization formulations are introduced to derive fast implementation algorithms inspired by powerful signal processing tools including sphere decoding and Viterbi algorithm, in both softand hard-decision versions. Extensive simulations testify the realistic performance of the proposed detectors in the presence of multiple access interference, timing synchronization errors and low-resolution digital-to-analog conversion.
This paper is devoted to turbo synchronization, that is to say the use of soft information to estimate parameters like carrier phase, frequency offset or timing within a turbo receiver. It is shown how maximum-likelihood estimation of those synchronization parameters can be implemented by means of the iterative expectation-maximization (EM) algorithm [1]. Then we show that the EM algorithm iterations can be combined with those of a turbo receiver. This leads to a general theoretical framework for turbo synchronization. The soft decision-directed ad-hoc algorithm proposed in [2] for carrier phase recovery turns out to be a particular instance of this implementation. The proposed mathematical framework is illustrated by simulations reported for the particular case of carrier phase estimation combined with iterative demodulation and decoding [3]. 2933 0-7803-7802-4/03/$17.00
The availability of flexible radio interfaces capable of adapting their configuration to the time-varying operating environment is the key response to the demand encountered in modern wireless networks for high data rates under strict quality of service (QoS) constraints. To this end, this paper develops a novel link resource adaptation (LRA) scheme for soft-decoded multiantenna (MIMO) bit interleaved coded orthogonal frequency division multiplexing (BIC-OFDM) transmissions employing automatic repeat request (ARQ) mechanisms. As the first step, a simple link performance evaluation model based on the effective signal-to-noise ratio (SNR) mapping concept is derived in a closed-form expression that it is shown to yield better accuracy than previous techniques. Then, an effective LRA strategy is formulated taking advantage of that framework. The aim is maximizing the goodput (GP) metric, that is to say, the number of information bits delivered without error to the user by unit of time, over the available radio resources, such as the power distribution on the subchannels, coding rate, modulation order and the MIMO configuration. The numerical results demonstrate considerable performance gains compared with nonadaptive transmissions, while keeping the computational complexity at affordable levels in view of the specific structure of the GP objective function
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2025 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.