This paper discusses the implementation of a very powerful but computationally efficient, iterative multi-user detector, intended for use as the basestation physical layer receiver for Wideband CDMA. This multiuser detector is unique in that it is fully compliant with the release '99 3GPP standard, a result that has not been shown before. The transmitter chain is discussed before the channel model used is introduced. The receiver design approach is then discussed. Special consideration is given to show how channel estimation is integrated into the receiver. We show single cell performance results that indicate a capacity increase of approximately three times over the "conventional" receiver implementation is possible (with and without antenna arrays). Results are then shown using a cell dimensioning simulation tool to indicate the overall gain in terms of increase in cell size. Here we can show that a gain of approximately 50% of the cell size is possible with such a multi-user detection approach. The dimensioning tool is also used to show the increase in capacity for a fixed cell size. Here we can show that a gain in the order of 330% is possible, compared to a conventional receiver approach.

This paper describes the operation of an iterative receiver for use on partial response signalling (PRS) channels. The data is convolutionally encoded and interleaved before being transmitted across the channel. An iterative receiver based on the turbo decoding principle is used to recover the data. Analysis and simulations confirm the exceptional performance of the receiver, with complexity independent of the memory of the channel. I. Introduction PRS channels have been found to be very useful for magnetic storage channels. The receiver size, however, grows exponential with the memory of the channel, adding complexity constraints. The concatenation of channel coding with the PRS channel has been previously described e.g. [1] as a method of improving performance due to coding gain. In this work we include channel coding not only to achieve coding gain improvements but to assist with equalisation of the PRS channel. Motivated by a recent iterative multi-user DS-CDMA receiver design [2...

Turbo codes, in the form of parallel concatenated convolutional codes, consist of two recursive systematic convolutional encoders separated by an interleaver. Due to the presence of the interleaver, each constituent convolutional encoder accepts as input a block of information bits with a size equal to that of the interleaver rather than a continuous stream of information bits. By determining the transfer function of each terminated constituent convolutional code, which can be seen as a convolutional block code, an upper bound to the bit error rate performance of the turbo code is readily calculated. In this paper, we briefly present the conventional techniques for evaluating the transfer function of the convolutional block code and we propose a novel technique, according to which the state diagram of the convolutional code is modified so as to allow the direct evaluation of the transfer function of the convolutional block code. 1

We present a novel maximum-likelihood (ML) joint frame synchronization and carrier phase ambiguity resolution algorithm for coded systems that exploits the code properties by accepting soft information from the MAP decoder. Simulation results are presented for turbo codes, and are compared to performance results of a conventional algorithm that does not use the code properties. We show that codeaided frame synchronization and phase ambiguity resolution is required for turbo codes, in order to avoid either significant BER degradations or the need for very long pilot sequences.

We investigate a sub-optimal reducedcomplexity iterative technique for joint detection and estimation for sets of constrained sequences and derive analytical results concerning convergence regions and xed points. We apply this theory to the problem of multiple-user decoding for multi-path fading channels.

Abstract — In recent years, it has been recognized that bitinterleaved coded modulation with iterative decoding (BICM-ID) achieves excellent performance on virtually any channel, provided the signal mapping is carefully designed. In this paper, we introduce multi-dimensional mapping for BICM-ID, where a group of bits is mapped to a vector of symbols, rather than a single symbol. This allows for more flexibility and potential performance improvements. Our analysis shows that multidimensional mapping leads to an increase in Euclidean distance, thus boosting the performance compared to conventional mapping schemes. We derive a design criterion for optimal mappings, and we provide such optimal mappings for BPSK and QPSK constellations. I.

The serial concatenation of simple error control codes and differential space-time modulation is considered. Decoding is performed iteratively by passing symbol-wise a-posteriori probability information between the decoders of the inner space-time code and the outer code. An input-output extrinsic information transfer analysis is used to predict thresholds for outer convolutional codes of various memory orders and simple outer parity check codes. It is shown that the simple parity check code is best matched to the inner differential space-time code and achieves a bit error rate of 10 −6 less than 2 dB from the Shannon capacity of the fast fading multiple antenna channel. The differential space-time code can also be used to generate a-priori information in the absence of channel knowledge. This information can be exploited by a channel estimator inserted into the decoding iteration. It is demonstrated that the inner space-time code provides soft training symbols from periodically inserted training symbols. The reliability of these soft training symbols does not depend on the speed of the channel variations, but on the structure of the inner code and the signal-to-noise ratio. Simulation studies confirm these findings and show that the proposed system with no initial channel knowledge achieves a performance very close to that of the system with perfect channel knowledge.

resolution

The serial concatenation of standard convolutional codes with di#erential spacetime modulation is considered for fast flat fading multiple antenna channels. Decoding is performed iteratively by passing symbol-wise a-posteriori probability information between the decoders of the inner space-time code and the outer convolutional code. An input-output extrinsic information transfer analysis is used to predict thresholds for outer codes of various memory orders. Simulation results show that this system can achieve bit error rates below 10 -4 at less than 2.5 dB from the Shannon capacity of the multiple antenna channel. # Supported in part by NSF Grants CCR 9732962 and ECS 9979323. 1 Concatenated Space-Time Coding: February 23, 2001 2 1

The performance of burst-by-burst adaptive modulation is studied in conjunction with reduced complexity turbo equalization over a wideband multi-path Rayleigh fading channel. By employing the reduced complexity turbo equalizer, higher-order modulation modes such as 64-level Quadrature Amplitude Modulation (64-QAM) can be invoked, than upon using the conventional turbo equalizer. The structure of the reduced complexity turbo equalizer was also exploited in order to invoke an iterative least mean square channel estimator. Finally, the performance of the adaptive modulation scheme was compared to that of its constituent modulation modes and a signal-to-noise ratio gain of ###dB to ###dB was recorded for the throughput range of 0.5 to 2.0 bits/symbol.