Turbo-Coded Adaptive Modulation Versus Space-Time Trellis Codes for Transmission over Dispersive Channels

Decision feedback equalizer (DFE)-aided turbocoded wideband adaptive quadrature amplitude modulation (AQAM) is proposed, which is capable of combating the temporal channel quality variation of fading channels. A procedure is suggested for determining the AQAM switching thresholds and the specific turbo-coding rates capable of maintaining the target bit-error rate while aiming for achieving a highly effective bits per symbol throughput. As a design alternative, we also employ multiple-input/multiple-output DFE-aided space–time trellis codes, which benefit from transmit diversity and hence reduce the temporal channel quality fluctuations. The performance of both systems is characterized and compared when communicating over the COST 207 typical urban wideband fading channel. It was found that the turbo-coded AQAM scheme outperforms the two-transmitter space–time trellis coded system employing two receivers; although, its performance is inferior to the space–time trellis coded arrangement employing three receivers. Index Terms—Coded adaptive modulation, dispersive channels, space–time trellis codes

Implementable Wireless Access for B3G Networks - III: Complexity Reducing Transceiver Structures

This article presents a comprehensive overview of some of the research conducted within Mobile VCE’s Core Wireless Access Research Programme,1 a key focus of which has naturally been on MIMO transceivers. The series of articles offers a coherent view of how the work was structured and comprises a compilation of material that has been presented in detail elsewhere (see references within the article). In this article MIMO channel measurements, analysis, and modeling, which were presented previously in the first article in this series of four, are utilized to develop compact and distributed antenna arrays. Parallel activities led to research into low-complexity MIMO single-user spacetime coding techniques, as well as SISO and MIMO multi-user CDMA-based transceivers for B3G systems. As well as feeding into the industry’s in-house research program, significant extensions of this work are now in hand, within Mobile VCE’s own core activity, aiming toward securing major improvements in delivery efficiency in future wireless systems through crosslayer operation

A New Reduced-Complexity Detection Scheme for Zero-Padded OFDM Transmissions

Recently, zero-padding orthogonal frequency division multiplexing (ZP-OFDM) has been proposed as an alternative solution to the traditional cyclic prefix (CP)-OFDM, to ensure symbol recovery regardless of channels nulls. Various ZP-OFDM receivers have been proposed in the literature, trading off performance with complexity. In this paper, we propose a novel low-complexity (LC) receiver for ZP-OFDM transmissions and derive an upper bound on the bit error rate (BER) performance of the LC-ZP-OFDM receiver. We further demonstrate that the LC-ZP-OFDM receiver brings a significant complexity reduction in the receiver design, while outperforming conventional minimum mean-square error (MMSE)-ZP-OFDM, supported by simulation results. A modified (M)-ZP-OFDM receiver, which requires the channel state information (CSI) knowledge at the transmitter side, is presented. We show that the M-ZP-OFDM receiver outperforms the conventional MMSE-ZP-OFDM when either perfect or partial CSI (i.e., limited CSI) is available at the transmitter side.Index Terms-Zero-padding, orthogonal frequency division multiplexing (OFDM), equalization

Adaptive antennas at the mobile and base stations in an OFDM/TDMA system

In recent years, several smart antenna systems have been proposed and demonstrated at the base station (BS) of wire-less communications systems, and these have shown that significant system performance improvement is possible. In this paper, we consider the use of adaptive antennas at the BS and mobile stations (MS), operating jointly, in combination with orthogonal frequency-division multiplexing. The advantages of the proposed system includes reductions in average error probability and increases in capacity compared to conventional systems. Multiuser access, in space, time, and through subcarriers, is also possible and expressions for the exact joint optimal antenna weights at the BS and MS under cochannel interference conditions for fading channels are derived. To demonstrate the potential of our proposed system, analytical along with Monte Carlo simulation results are provided

Near far resistant detection for CDMA personal communication systems.

The growth of Personal Communications, the keyword of the 90s, has already the signs of a technological revolution. The foundations of this revolution are currently set through the standardization of the Universal Mobile Telecommunication System (UMTS), a communication system with synergistic terrestrial and satellite segments. The main characteristic of the UMTS radio interface, is the provision of ISDN services. Services with higher than voice data rates require more spectrum, thus techniques that utilize spectrum as efficiently as possible are currently at the forefront of the research community interests. Two of the most spectrally efficient multiple access technologies, namely. Code Division Multiple Access (CDMA) and Time Division Multiple Access (TDMA) concentrate the efforts of the European telecommunity.This thesis addresses problems and. proposes solutions for CDMA systems that must comply with the UMTS requirements. Prompted by Viterbi's call for further extending the potential of CDMA through signal processing at the receiving end, we propose new Minimum Mean Square Error receiver architectures. MMSE detection schemes offer significant advantages compared to the conventional correlation based receivers as they are NEar FAr Resistant (NEFAR) over a wide range of interfering power levels. The NEFAR characteristic of these detectors reduces considerably the requirements of the power control loops currently found in commercial CDMA systems. MMSE detectors are also found, to have significant performance gains over other well established interference cancellation techniques like the decorrelating detector, especially in heavily loaded system conditions. The implementation architecture of MMSE receivers can be either Multiple-Input Multiple Output (MIMO) or Single-Input Single-Output. The later offers not only complexity that is comparable to the conventional detector, but also has the inherent advantage of employing adaptive algorithms which can be used to provide both the dispreading and the interference cancellation function, without the knowledge of the codes of interfering users. Furthermore, in multipath fading channels, adaptive MMSE detectors can exploit the multipath diversity acting as RAKE combiners. The later ability is distinctive to MMSE based receivers, and it is achieved in an autonomous fashion, without the knowledge of the multipath intensity profile. The communicator achieves its performance objectives by the synergy of the signal processor and the channel decoder. According to the propositions of this thesis, the form of the signal processor needs to be changed, in order to exploit the horizons of spread spectrum signaling. However, maximum likelihood channel decoding algorithms need not change. It is the way that these algorithms are utilized that needs to be revis ed. In this respect, we identify three major utilization scenarios and an attempt is made to quantify which of the three best matches the requirements of a UMTS oriented CDMA radio interface. Based on our findings, channel coding can be used as a mapping technique from the information bit to a more ''intelligent" chip, matching the ''intelligence" of the signal processor

A Mobile Wireless Channel State Recognition Algorihm: Introduction, Definition, and Verification - Sensing for Cognitive Environmental Awareness

This research includes mobile wireless systems limited by time and frequency dispersive channels. A blind mobile wireless channel (MWC) state recognition (CSR) algorithm that detects hidden coherent nonselective and noncoherent selective processes is verified. Because the algorithm is blind, it releases capacity based on current channel state that traditionally is fixed and reserved for channel gain estimation and distortion mitigation. The CSR algorithm enables cognitive communication system control including signal processing, resource allocation/deallocation, or distortion mitigation selections based on channel coherence states. MWC coherent and noncoherent states, ergodicity, stationarity, uncorrelated scattering, and Markov processes are assumed for each time block. Furthermore, a hidden Markov model (HMM) is utilized to represent the statistical relationships between hidden dispersive processes and observed receive waveform processes. First-order and second-order statistical extracted features support state hard decisions which are combined in order to increase the accuracy of channel state estimates. This research effort has architected, designed, and verified a blind statistical feature recognition algorithm capable of detecting coherent nonselective, single time selective, single frequency selective, or dual selective noncoherent states. A MWC coherence state model (CSM) was designed to represent these hidden dispersive processes. Extracted statistical features are input into a parallel set of trained HMMs that compute state sequence conditional likelihoods. Hard state decisions are combined to produce a single most likely channel state estimate for each time block. To verify the CSR algorithm performance, combinations of hidden state sequences are applied to the CSR algorithm and verified against input hidden state sequences. State sequence recognition accuracy sensitivity was found to be above 99% while specificity was determined to be above 98% averaged across all features, states, and sequences. While these results establish the feasibility of a MWC blind CSR algorithm, optimal configuration requires future research to further improve performance including: 1) characterizing the range of input signal configurations, 2) waveform feature block size reduction, 3) HMM parameter tracking, 4) HMM computational complexity and latency reduction, 5) feature soft decision combining, 6) recursive implementation, 7) interfacing with state based mobile wireless communication control processes, and 8) extension to wired or wireless waveform recognition