Parallel Interference Cancellation Algorithm Research Articles

A novel iterative detection method based on a lattice reduction-aided algorithm for MIMO OFDM systems

The lattice reduction-aided algorithm has received broad attention from researchers since it operates as a maximum likelihood receiver with better system performance for multiple-input multiple-output orthogonal frequency division multiplexing systems and contains a full diversity. A novel iterative detection algorithm canceling parallel iterations that employ the lattice reduction-aided approach is proposed. Soft information is exchanged through the detector itself. Its iteration occurs inside the detector, which reduces much of the exchange cost between the multiple-input multiple-output orthogonal frequency division multiplexing detector and the turbo decoder. Since the parallel interference cancellation algorithm is constrained by the accuracy of the initial value of the detection, it is easy to form error propagation after several iterations. Due to the lattice reduction-aided algorithm, its performance is approximated with the maximum likelihood algorithm. Therefore, the lattice reduction-aided algorithm is introduced into the parallel interference cancellation algorithm to make its detection algorithm more accurate and overcome the effect of error propagation in the manuscript. Simulation results indicate that the proposed algorithm leads to an improvement of 0.8–2 dB when the bit error rate is set to 10–4 when compared to other algorithms.

An intelligent reflecting surfaces based iterative PhC‐MIMO system for atmospheric optical channels

AbstractOptical intelligent reflecting surface (IRS) is regarded as a forward‐looking technology to deal with line‐of‐sight limitations in optical wireless communications. This paper proposes an iterative photon counting nonorthogonal multiple access‐multiple‐input–multiple‐output (NOMA‐MIMO) system based on optical IRS. By analyzing the geometric and misalignment losses under turbulence effect in the optical IRS‐based atmospheric channel, we construct the channel fading coefficient matrix of the NOMA‐MIMO system. At the receiver, a novel iterative parallel interference cancellation algorithm based on logarithmic likelihood ratio is developed for signal detection. Through the simulation of bit error rate (BER), the reliability of the proposed system is proved. Quantitatively, the BER performance can achieve at the dBJ per bit for the scenario of MIMO system. Furthermore, the numerical results of the external information transfer process indicated that the proposed system has a rapid convergence performance.

Deep Learning Network for Multiuser Detection in Satellite Mobile Communication System.

A multiuser detection (MUD) algorithm based on deep learning network is proposed for the satellite mobile communication system. Due to relative motion between the satellite and users, multiple access interference (MUI) introduced by multipath fading channel reduces system performance. The proposed MUD algorithm based on deep learning network firstly establishes the CINR optimal loss function according to the multiuser access mode and then obtains the best multiuser detection weight through the steepest gradient iteration. Multilayer nonlinear learning obtains interference cancellation sharing weights to achieve maximum signal-to-noise ratio through gradient iteration, which is superior than the traditional serial interference cancellation algorithm and parallel interference cancellation algorithm. Then, the weights with multiuser detection through multilayer network forward learning iteration are obtained with traditional multiuser detecting quality characteristics. The proposed multiuser access detection based on deep learning network algorithm improves the MUD accuracy and reduces the number of traditional multiusers. The performance of the satellite multifading uplink system shows that the proposed deep learning network can provide high precision and better iteration times.

Improved Uplink NOMA Performance Through Adaptive Weighted Factors Aided PIC and MA Signature

Non-orthogonal multiple access (NOMA) is one innovative technology that provides low latency, high system capacity, high spectrum efficiency, and massive connectivity to solve several challenges suffered by a fifth generation (5G) mobile communication system. NOMA on the uplink with superior research value was widely mentioned at Mobile World Congress and has been released in the latest technical report by the Third Generation Partnership Project (3GPP). However, how to decode all users' signals on the uplink NOMA precisely and in parallel and achieve the separation of the superimposed users' signals is the major challenge. Therefore, an improved uplink NOMA scheme through adaptively weighted factors aided parallel interference cancellation (PIC) algorithm and multiple access (MA) signature is proposed to solve the problem. In this paper, we first briefly discuss the research status of the MA signatures used to separate superimposed users' signals. In addition, we review the existing interference cancellation algorithms used by receivers to decode message signals, which mainly include a successive interference cancellation (SIC) algorithm and the PIC algorithm. And the research value of the PIC algorithm on uplink NOMA is highlighted. Then, we briefly formulate the effect of the bias in decision statistics and adaptive weighted factors aided PIC algorithm is proposed to reduce the biased estimation. Finally, yet important, we comprehensively evaluate the performance of the proposed improving PIC algorithm in terms of bit error rate (BER), computational complexity, sum data rate, and delay estimation errors.

Distributed Signal Compressive Quantization and Parallel Interference Cancellation for Cloud Radio Access Network

The explosive growth of wireless traffic requires revolutionary wireless communication techniques. The cloud radio access network (C-RAN) is a solution to leverage the spatial multiplexing gain by utilizing a number of antennas distributed in a certain area. However, in most of the current literature, due to the limited front-haul capacity, each remote radio head (RRH) can use only a single antenna, and thus the total number of antennas can be utilized are limited. In this work, we propose a distributed baseband signal compressive quantization scheme for the uplink of a multi-antenna C-RAN where each RRH uses multiple antennas. At each RRH, the baseband signals of multiple time instants are embedded into a vector with low dimension using delay-and-add so that more bits can be allocated to each value, and the quantization noise power caused by the front-haul link capacity deficit is reduced. The delay-and-add operation is low complexity that can be realized using basic buffering and adding, and it does not require channel information in the RRHs. Therefore, the low deployment cost feature of C-RAN is preserved. As a result, a large number of antennas can be utilized by deploying a lot of multi-antenna RRHs, which provide rich spatial diversity that assists the detection which happens in the baseband units. In the symbol detection phase, the corresponding weight vectors are designed to detect the symbols from the compressive quantized baseband signal. A parallel interference cancellation algorithm is proposed to further improve the accuracy of the symbol detection. Numerical results show that the proposed scheme is efficient in tackling the front-haul capacity challenge. We also apply the proposed scheme to orthogonal frequency-division multiplexing-based multi-antenna C-RAN, where we find that the system can utilize larger bandwidth with limited front-haul capacity. It facilitates the deployment of C-RAN based on both 4G and 5G wireless communications.

Multi-Stage Partial Parallel Interference Cancellation Algorithm for MUSA Systems

Multi-User Shared Access is a non-orthogonal multiple access scheme of 5G,which has a high computational complexity and a large time delay due to the usage of successive interference cancellation detection algorithm. This paper proposes a multi-stage partial parallel interference cancellation detection algorithm, which does not require repeated ordering and repeated matrix inversion. In the first stage of detection, the bits of these users with good channel conditions will be outputted, and the influence of multiple access interference on users with bad channel conditions in the second stage will be decreased. Theoretical analysis and simulation results show that the symbol error rate of the proposed algorithm is slightly better than that of the two-stage MMSE-PIC, and the complexity is reduced. In the meanwhile, the computational complexity is significantly reduced without SER performance degradation when compared with MMSE-SIC algorithm.

R-OFDM for RGBA-LED-Based Visible Light Communication With Illumination Constraints

This paper proposes a reshaped orthogonal frequency division multiplexing (R-OFDM) scheme for intensity modulation/direct detection visible light communication (VLC) systems, where an LED consisting of red, green, blue, and amber chips (RGBA-LED) is adopted as the transmitter. In R-OFDM, the signal is adjusted by signal separation and biasing after clipping (BAC)/scaling before clipping (SBC) operations for transmitting in the RGBA-LED. We optimize both biasing and scaling factors for the BAC and SBC operations, respectively. Correspondingly, a direct detection algorithm is developed for data recovery at receiver. Theoretical bit error rate (BER) performance of the proposed R-OFDM scheme is further analyzed. Specifically for the multicolor LED transmission, a low complexity parallel interference cancellation algorithm is also proposed for eliminating the interference caused by cross-talk in multicolor VLC channels. Numerical results over practical optical channels are presented to validate the advantage of the proposed R-OFDM scheme. It is revealed that the R-OFDM achieves noticeable performance gain in term of BER than the conventional Flip-OFDM and ACO-OFDM.

A Blind Adaptive Kalman-PIC MUD Algorithm for the Multiple Access Communication Network

In the parallel signal processing, the multi-user detection precision of parallel interference cancellation (PIC) detector is always easily affected by the decision error diffusion. Based on the fast convergence and low complexity of blind adaptive Kalman algorithm, a new blind adaptive Kalman-PIC (KPIC) multi-user detection (MUD) algorithm is proposed for the direct sequence spread spectrum code division multiple access (DS-CDMA) system network with strong multiple access interference (MAI). Compared with traditional standard Kalman filter and PIC algorithm, the proposed combined program can totally track the time-varying channel, effectively estimate unknown noise statistics characteristics on-line while conducting state filtering, possibly minimize the detection error diffusion in the interference cancellation processing of single PIC algorithm, thus effectively suppress MAI. Simulation results show that the KPIC algorithm is of better convergence, dynamic tracking ability and precision

Efficient parallel interference cancellation algorithm for multiuser detection schemes in CDMA-based 20.48-Gb/s optical MIMO-OFDM system over 1200 km of SSMF

This paper presents an efficient algorithm to cancel the parallel interference for multiuser detection (MUD) schemes in code division multiple access (CDMA) based 20.48Gb/s optical multiple input multiple output orthogonal frequency division multiplexing (O-MIMO-OFDM) system over 1200km of standard single mode fiber (SSMF). The performance of the system is compared by simulation results using the efficient algorithm and minimum mean square error (MMSE) schemes. It shows the superior performance of efficient algorithm.

Pre-processing Matrix Based Iterative Detection Algorithm in Asynchronous MIMO-OFDM

In asynchronous MIMO-OFDM over the selective Rayleigh fading channel, an iterative parallel multi- antenna interference cancellation algorithm based on pre-processing matrix is proposed. Before the signal is transmitted, the symbols are spread over all the subcarriers, which relieve the influence of deep fading in part of the subcarriers. In the receiver, the wrong decision value of last iteration is spread by the pre-processing matrix, which decrease the error propagation in iteration processing. The performance improvement is verified by simulation, when there are 4 transmitters 2 receivers and the Bit Error Rate (BER) is 10-5, SNR is improved about 4.5 dB compared with the traditional iterative parallel interference cancellation algorithm.

ASIC Implementation of Soft-Input Soft-Output MIMO Detection Using MMSE Parallel Interference Cancellation

Multiple-input multiple-output (MIMO) technology is the key to meet the demands for data rate and link reliability of modern wireless communication systems, such as IEEE 802.11n or 3GPP-LTE. The full potential of MIMO systems can, however, only be achieved by means iterative MIMO decoding relying on soft-input soft-output (SISO) data detection. In this paper, we describe the first ASIC implementation of a SISO detector for iterative MIMO decoding. To this end, we propose a low-complexity minimum mean-squared error (MMSE) based parallel interference cancellation algorithm, develop a suitable VLSI architecture, and present a corresponding four-stream 1.5 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> detector chip in 90 nm CMOS technology. The fabricated ASIC includes all necessary preprocessing circuitry and exceeds the 600 Mb/s peak data-rate of IEEE 802.11n. A comparison with state-of-the-art MIMO-detector implementations demonstrates the performance benefits of our ASIC prototype in practical system-scenarios.

Performance analysis of an adaptive two-stage PIC CDMA receiver in AWGN channels

Parallel interference cancellation (PIC) is considered a simple yet effective multiuser detector for direct-sequence code-division multiple-access (DS-CDMA) systems. However, its performance may deteriorate due to unreliable interference cancellation in the early stages. Thus, a partial PIC detector, in which partial cancellation factors (PCFs) are introduced to control the interference cancellation level, has been developed as a remedy. Recently, an interesting adaptive multistage PIC algorithm was proposed. In this scheme, coefficients combining the channel responses and optimal PCFs are blindly trained with the least mean square (LMS) algorithm. The algorithm is simple to implement, inherently applicable to time-varying environments, and superior to the non-adaptive type of partial PICs. Despite its various advantages, its performance has not been theoretically analyzed yet. The contribution of this paper is to fill the gap by analyzing an adaptive two-stage PIC in AWGN channels. We explicitly derive the analytical results for optimal weights, weight-error means, and weight-error variances. Based on these results, we finally derive the output bit error rate (BER) for each user. Simulation results indicate that our analytical results highly agree with empirical ones.

Low-Complexity Turbo Equalization and Multiuser Decoding for TD-CDMA

The authors propose a low complexity multiuser joint parallel interference cancellation (PIC) decoder and turbo decision feedback equalizer for code division multiple access (CDMA). In their scheme, an estimate of the interference signal (both multiple-access interference and intersymbol interference) is formed by weighting the hard decisions produced by conventional (i.e., hard-output) Viterbi decoders. The estimated interference is subtracted from the received signal in order to improve decoding in the next iteration. By using asymptotic performance analysis of random-spreading CDMA, they optimize the feedback weights at each iteration. Then, they consider two (mutually related) performance limitation factors: the bias of residual interference and the ping-pong effect. The authors show that the performance of the proposed algorithm can be improved by compensating for the bias in the weight calculation, and they propose a modification of the basic PIC algorithm, which prevents the ping-pong effect and allows higher channel load and/or faster convergence to the single-user performance. The proposed algorithm is validated through computer simulation in an environment fully compliant with the specifications of the time-division duplex mode of third-generation systems, contemplating a combination of time-division multiple access and CDMA and including frequency-selective fading channels, user asynchronism, and power control. The main conclusion of this work is that, for such application, soft-input soft-output decoders (e.g., implemented by the forward-backward BCJR algorithm) are not needed to attain very high spectral efficiency, and simple conventional Viterbi decoding suffices for most practical settings.