PAPR Constrained Power Allocation for Iterative Frequency Domain Multiuser SIMO Detector

Peak to average power ratio (PAPR) constrained power allocation in single carrier multiuser (MU) single-input multiple-output (SIMO) systems with iterative frequency domain (FD) soft cancelation (SC) minimum mean squared error (MMSE) equalization is considered in this paper. To obtain full benefit of the iterative receiver, its convergence properties need to be taken into account also at the transmitter side. In this paper, we extend the existing results on the area of convergence constrained power allocation (CCPA) to consider the instantaneous PAPR at the transmit antenna of each user. In other words, we will introduce a constraint that PAPR cannot exceed a predetermined threshold. By adding the aforementioned constraint into the CCPA optimization framework, the power efficiency of a power amplifier (PA) can be significantly enhanced by enabling it to operate on its linear operation range. Hence, PAPR constraint is especially beneficial for power limited cell-edge users. In this paper, we will derive the instantaneous PAPR constraint as a function of transmit power allocation. Furthermore, successive convex approximation is derived for the PAPR constrained problem. Numerical results show that the proposed method can achieve the objectives described above.Comment: Presented in IEEE International Conference on Communications (ICC) 201

Low Complexity Time-Concatenated Turbo Equalization for Block Transmission Without Guard Interval: Part 1—The Concept

This paper proposes a novel time-concatenated turbo equalization technique, chained turbo equalization (CHATUE), that allows block transmission systems to eliminate the guard interval (GI), while achieving excellent performance. The proposed CHATUE algorithm connects turbo equalizers neighboring in time, so that they exchange information about their inter-block-interference components in the form of a posteriori log-likelihood ratio. The latest version of the low complexity sub-optimal turbo equalization technique for block-wise single carrier transmission, frequency domain soft cancellation and minimum mean squared error, is fully exploited in developing the CHATUE algorithm. Results of extrinsic information transfer chart analysis as well as a series of bit-error rate (BER) simulations show that excellent performances can be achieved without imposing heavy computational burden in multipath-rich (quasi-static) block Rayleigh fading channels. It is shown that, if the information bit-rate is kept identical (because it may be unpreferable for the industry to change the frame structure), the CHATUE algorithm achieves lower BER than that with block transmission with GI, because lower rate (strong) code for error protection can be used by utilizing the time-duration made available by eliminating the GI. In addition, by combining the proposed structure with a simple rate-1 doped accumulator, further BER improvement exhibiting clear turbo cliff can be achieved. A sister paper (a Part-2 paper) applies the proposed CHATUE algorithm to single carrier frequency division multiple access systems Hui et al. (Wirel Pers Commun, 2011)

Estimation of Space-Time Varying Channels Using Signal Subspace Projection and Soft Information

We consider the uplink of a time-slotted wireless communication system with a mobile user and a base station equipped with an antenna array of M elements. The space-time varying channel of the system is usually estimated using training sequence in each slot and refined by projecting it to the corresponding spatial signal subspace. However, this method does not work when the space-time channel matrix is full row rank. In this paper, we formulate the channel by a Sylvester matrix using the space-time signal model for this full row rank case and propose a channel estimation method based on the space-time signal subspace projection. We also propose a channel estimation method that incorporates the extended training symbols by the soft information fed back from the decoder to improve the channel estimation performance. Numerical results show that these two methods can be performed separately or jointly to improve the performance of the space-time channel estimation by training sequences.2011 International Conference on Acoustics, speech, and signal processing, Prague, Czech Republic, May 22-27 2011

Chained Turbo Equalization for SC-FDMA Systems without Cyclic Prefix

This paper proposes a novel Single Carrier Frequency Division Multiple Access (SC-FDMA) System without Cyclic Prefix based on the Chained Turbo Equalization (CHATUE) algorithm, which connects turbo equalizers neighboring in time to eliminate the Inter-Block Interference (IBI). Results of Extrinsic Information Transfer (EXIT) chart demonstrate that the performance can be improved by performing iterations between neighboring blocks. In addition, this paper also proposes a complexity reduction technique. The numerical results verify the performance improvement and superiority of the proposed technique over the conventional SC-FDMA transmission, without requiring high computational complexity

Simple Coded Amplify-and-Forward Two-Way Relay Systems with Imperfect Side Information

This paper proposes a very simple, near capacity achieving coding scheme for an amplify-and-forward two-way relaying system with imperfect side information, in which two sources communicate with their respective destinations with the help of one relay. To avoid heavy computational complexity at the destinations, we assume a very short memory convolutional code. At the destinations iterative decoding between Joint-over- Antennas (JA) demapper and channel decoder is used to separate and decode the two signals. We present extrinsic information transfer (EXIT) chart analysis of the system. It is shown that demapper and decoder EXIT curves intersect each other before (1, 1) mutual information (MI) point, causing an error floor in the bit-error-rate (BER) performance. With a rate-1 doped accumulator (D-Acc) following the short memory convolutional encoder via an interleaver, the demapper curve and the decoder curve match very well, and the convergence tunnel opens until the (1,1) MI point, and thus the error floor can be completely removed. Simulations were conducted in two cases: without side information, and with imperfect side information. Simulation results show that in case of no side information turbo cliff happens at 1.25 dB away from the Shannon limit of a single link. With the help of side information, cliff happens at a value of received signal-to-noise power ratio even closer to the limit

EXIT Chart-Based Power Allocation for Iterative Frequency Domain MIMO Detector

Transmission power allocation in single-carrier　multiple-input multiple-output (MIMO) systems with iterative frequency-domain (FD) soft cancellation (SC) minimum　mean-squared error (MMSE) equalization is considered. A novel framework for transmission power minimization subject to equalizer convergence constraints, referred as convergence constrained power allocation (CCPA) method, is proposed based on extrinsic information transfer (EXIT) chart analysis. The proposed method decouples the spatial interference between the streams using singular value decomposition (SVD), and minimizes the transmission power while achieving the target mutual information for each stream after iterations at the receiver. We show that the transmission power optimization can be formulated as a convex optimization problem. Three CCPA methods, one approximately optimal, and other two heuristic methods inspired by the Lagrange duality are derived. The numerical results demonstrate that the proposed scheme outperforms the existing linear precoding schemes. Moreover, the proposed heuristic schemes can achieve performance close with that of the approximately optimal method in terms of the equalizer convergence properties as well as transmission power

SemantIC: Semantic Interference Cancellation Towards 6G Wireless Communications

This letter proposes a novel anti-interference technique, semantic interference cancellation (SemantIC), for enhancing information quality towards the sixth-generation (6G) wireless networks. SemantIC only requires the receiver to concatenate the channel decoder with a semantic auto-encoder. This constructs a turbo loop which iteratively and alternately eliminates noise in the signal domain and the semantic domain. From the viewpoint of network information theory, the neural network of the semantic auto-encoder stores side information by training, and provides side information in iterative decoding, as an implementation of the Wyner-Ziv theorem. Simulation results verify the performance improvement by SemantIC without extra channel resource cost

On Greedy Methods for EXIT Chart Based Transmission Power Allocation

This paper addresses the problem of power allocation for single carrier point-to-point multiple input multiple output (MIMO) systems with iterative frequency-domain (FD) soft cancellation (SC) minimum mean squared error (MMSE) equalization. Two novel heuristic power allocation methods are proposed. The proposed methods explicitly take into account the convergence properties of the iterative equalizer while transmission power is minimized. The proposed heuristic schemes are based on, convergence constraint power allocation (CCPA), technique that decouples the spatial interference between streams using singular value decomposition (SVD), and minimize the transmission power while achieving the target mutual information for each stream after iterations at the receiver side. The proposed heuristic transmission schemes are inspired by well-known greedy algorithm resulting in a simple and efficient solutions to the power allocation problem. Numerical results show that the proposed heuristic schemes can achieve close to optimal performance in the terms of equalizer convergence as well as the total transmission power