Transmission performance of layered-symbol iterative interference cancellation for single-carrier MIMO multiplexing

Orthogonal time-frequency space(OTFS) is a two-dimensional modulation technology that enables efficiently operating on high-mobility wireless channels. However, the high dimension of the channel matrix in the multi-input multi-output(MIMO) OTFS system makes it challenging to design high-performance equalizers. In this paper, the block linear minimum mean squared error(LMMSE) equalizers are proposed for MIMO diversity and MIMO multiplexing. We first place zero-padding(ZP) to the OTFS's frame and get the sparse time domain channel matrix with submatrices arranged diagonally. Then we reduce the time domain input-output relation to the submatrices form in the MIMO-OTFS system. Finally, we equalize the receiving information based on the MMSE criterion. Simulation demonstrates that the proposed equalizer performs better with about 2dB gain over the conventional MMSE equalizer at a bit-error-rate(BER) of 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-5</sup> for MIMO diversity, while the proposed equalizer is more applicable to practical work with the advantage of low-complexity.

Channel coding is a fundamental procedure in wireless telecommunication systems and has a strong impact on the data transmission quality. This effect becomes more important when the transmission must be characterised by low latency and low bit error rate, as in the case of vehicle-to-everything (V2X) services. Thus, V2X services must use powerful and efficient coding schemes. In this paper, we thoroughly examine the performance of the most important channel coding schemes in V2X services. More specifically, the impact of use of 4th-Generation Long-Term Evolution (4G-LTE) turbo codes, 5th-Generation New Radio (5G-NR) polar codes and low-density parity-check codes (LDPC) in V2X communication systems is researched. For this purpose, we employ stochastic propagation models that simulate the cases of line of sight (LOS), non-line of sight (NLOS) and line of sight with vehicle blockage (NLOSv) communication. Different communication scenarios are investigated in urban and highway environments using the 3rd-Generation Partnership Project (3GPP) parameters for the stochastic models. Based on these propagation models, we investigate the performance of the communication channels in terms of bit error rate (BER) and frame error rate (FER) performance for different levels of signal to noise ratio (SNR) for all the aforementioned coding schemes and three small V2X-compatible data frames. Our analysis shows that turbo-based coding schemes have superior BER and FER performance than 5G coding schemes for the vast majority of the considered simulation scenarios. This fact, combined with the low-complexity requirements of turbo schemes for small data frames, makes them more suitable for small-frame 5G V2X services.

Polar codes are the first provably capacity-achieving forward error correction codes. To improve decoder throughput, the symbol-decision SC algorithm makes hard-decision for multiple bits at a time. In this paper, we prove that for polar codes, the symbol-decision SC algorithm is better than the bit-decision SC algorithm in terms of the frame error rate (FER) performance because the symbol-decision SC algorithm performs a local maximum likelihood decoding within a symbol. Moreover, the bigger the symbol size, the better the FER performance. Finally, simulation results over both the additive white Gaussian noise channel and the binary erasure channel confirm our theoretical analysis.

This paper uses the reconstruction-computation-quantization (RCQ)paradigm to decode low-density parity-check (LDPC) codes. RCQ facilitates dynamic non-uniform quantization to achieve good frame error rate (FER) performance with very low message precision. For message-passing according to a flooding schedule, the RCQ parameters are designed by discrete density evolution. Simulation results on an IEEE 802.11 LDPC code show that for 4-bit messages, a flooding Min Sum RCQ decoder outperforms table-lookup approaches such as information bottleneck (IB) or Min-IB decoding, with significantly fewer parameters to be stored. Additionally, this paper introduces layer-specific RCQ, an extension of RCQ decoding for layered architectures. Layer-specific RCQ uses layer-specific message representations to achieve the best possible FER performance. For layer-specific RCQ, this paper proposes using layered discrete density evolution featuring hierarchical dynamic quantization (HDQ) to design parameters efficiently. Finally, this paper studies field-programmable gate array (FPGA) implementations of RCQ decoders. Simulation results for a (9472, 8192) quasi-cyclic (QC) LDPC code show that a layered Min Sum RCQ decoder with 3-bit messages achieves more than a 10% reduction in LUTs and routed nets and more than a 6% decrease in register usage while maintaining comparable decoding performance, compared to a 5-bit offset Min Sum decoder.

Physical-layer security offers low probability of interception (LPI) in wireless communication systems. While prior methods such as the directional beamforming and secrecy coding schemes require knowledge of the eavesdropper (Eve)’s channel, passive eavesdropping limits their practicality. Artificial additive noise and artificial fast fading (AFF) schemes address the issue by degrading detection ability of a potential Eve without knowing its channel information. In particular, AFF achieves LPI by effectively shortening the coherence time of Eve’s channel using a random precoder while keeping the legitimate receiver (Bob)’s channel deterministic. In this paper, we propose a novel AFF design for spatial multiplexing multi-input multi-output (MIMO) amplify-and-forward (AF) relay systems. First, we formulate an optimization problem to achieve minimum mean squared error (MMSE) of Bob’s signals while guaranteeing LPI conditions from Eve, which is generally non-convex. To tackle the non-convexity of the problem, we apply a convex set approximation technique and thereby derive a simple closed-form design. Finally, we evaluated the performance of both Bob and Eve via computer simulations to demonstrate the effectiveness of our proposed design.

Polar codes under cyclic redundancy check-aided successive cancellation list (CA-SCL) decoding can outperform the turbo codes and the LDPC codes when code lengths are configured to be several kilobits. In order to reduce the decoding complexity, a novel tree-pruning scheme for the SCL/CA-SCL decoding algorithms is proposed in this letter. In each step of the decoding procedure, the candidate paths with metrics less than a threshold are dropped directly to avoid the unnecessary computations for the path searching on the descendant branches of them. Given a candidate path, an upper bound of the path metric of its descendants is proposed to determined how much pruning this candidate path would affect frame error rate (FER) performance. By utilizing this upper bounding technique and introducing a dynamic threshold, the proposed scheme deletes as many as possible of the redundant candidate paths while keeping the performance deterioration in a tolerant region, thus it is much more efficient than the existing pruning scheme. With only a negligible loss of FER performance, the computational complexity of the proposed pruned decoding scheme is only about 40% of the standard algorithm in the low signal-to-noise ratio (SNR) region (where the FER under CA-SCL decoding is about 0.1 ~ 0.001), and it can be very close to that of the successive cancellation (SC) decoder in the moderate- and high-SNR regions.

The inner decoder of the Davey-MacKay (DM) construction for combating insertions, deletions and substitution errors, has high complexity and produces bursts of output likelihoods of greatest uncertainty in the vicinity of insertions and deletions. We therefore propose (i) a lookup-table-based implementation of the inner decoder to reduce its complexity, (ii) the use of interleaved LDPC codes as outer codes in the DM construction to spread the uncertain likelihoods produced by the inner decoder over several constituent LDPC codewords. Simulation results show that the proposed lookup table approach reduces the complexity of the inner decoder considerably while a significant improvement in frame error rate (FER) performance can be obtained with small interleaving depths. Our lookup table approach culminates in an iterative decoding scheme which yields improved FER performance over its non-iterative counterparts, yet with only a modest increase in decoding complexity, when the insertion/deletion probability is small.

This paper proposes a new iterative interference canceller (IIC) with log-likelihood ratio (LLR) compensation for low-density parity-check (LDPC) coded multi-input multi-output (MIMO) systems in order to mitigate the influence of error propagation. The proposed IIC compensates the LLR, which is obtained from the LDPC decoding, by adding the LLR obtained at previous turns of iteration. Computer simulation results show that the proposed the IIC with LLR compensation can obtain 3dB of Eb/N0 gain for achieving WER=10 -3 compared with the IIC without LLR compensation and requires less than 1dB of additional Eb/N0 compared with the maximum a posteriori (MAP) demodulator.

This paper focuses on the compensation of carrier frequency offsets (CFO) for spatial multiplexing multi-input multi-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems with distributed transmit antennas, where the CFOs between the receiver and each transmit antenna are possibly different and the zero-forcing (ZF) detection is used. Rather than the conventional linear frequency-domain equalization method that involves computationally complex matrix inversions, we propose a CFO compensation method without need for matrix inversion by exploiting the underlying characteristics of ZF detection and assuming relatively small root-mean-square (r.m.s.) delay spread of the multipath channel. Simulation results show that the symbol error rate (SER) performance of the system is significantly improved by using the proposed CFO compensation method in the low delay spread case (i.e., channel A) of the three test environments in the ITU-R M.1225 channel model.

In this paper, anew iterative interference cancellation multiuser detection (MUD) method is proposed for overloaded multiple-input multiple-output (MIMO) coded orthogonal frequency division multiplexing (OFDM) systems. In the first iteration, a channel analyzer and selector are employed, which ensure that non-convergent channels are not used. Then low complexity RAKE reception is applied, and a successive interference cancellation (SIC)-based approach is used such that the strongest user is decoded first. In each iteration, the soft output of the convolutional decoder is fed back to cancel inter-user interference using parallel interference cancellation (PIC). The simulation results show that, this technique can achieve near-optimum bit error rate (BER) performance, and optimum frame error rate (FER) performance, with lower complexity than optimum maximum likelihood (ML) methods at the cost of 4% of channels rejected.

In this paper, we study the block error rate (BLER) performance of spatially coupled low-density parity-check (SC-LDPC) codes using a sliding window decoder suited for streaming applications. Previous studies of SC-LDPC have focused on the bit error rate (BER) performance or the frame error rate (FER) performance over the entire length of the code. Here, we consider protograph-based constructions of SC-LDPC codes in which a window decoder continuously outputs blocks in a streaming fashion, and we examine the BLER associated with these blocks. We begin by examining the effect of protograph design on the streaming BLER by varying the block size and the coupling width in such a way that the overall constraint length of the SC-LDPC code remains constant. Next, we investigate the BLER scaling behavior with block size and coupling width. Lastly, we consider the effect of employing an outer code to protect blocks, so that small numbers of residual errors can be corrected by the outer code. Simulation results for the additive white Gaussian noise channel (AWGNC) are included and comparisons are made to LDPC block codes (LDPC-BCs).

In this contribution, we investigate the performance of dual-polarized multi input multi output (MIMO) multi-carrier interleave division multiple access system (MC-IDMA) over correlated frequency selective channels in the presence of channel state estimation error. In the code division multiple access (CDMA), orthogonal spreading sequence is used as user specific where as in IDMA, user specific interleaving pattern is used. In our considered work, Multi-carrier (MC) is realized by orthogonal frequency division multiplexing (OFDM). The channel is estimated at the mobile stations (MSs) by pilot assisted channel estimation (PACE) technique using minimum mean square error (MMSE) algorithm. Further, the dual-polarized MIMO system considered in our work which is realized with the aid of orthogonal polarizations, replaces two spatially separated uni-polarized antennas, thus resulting in polarization multiplexing. In particular, we evaluate the effects of three types of delay spread on MIMO MC-IDMA system in the context of downlink (DL) communications pertaining to the Standard University Interim (SUI) channel model. In a multi-user environment, users experience multi stream interference (MSI) in addition to the multiple access interference (MAI) and these interferences can degrade the system performance. Furthermore, we consider turbo code as channel encoder for MIMO MC-IDMA system to mitigate the effects of MAI and MSI. It is discerned from the simulation results that dual-polarized MIMO MC-IDMA system is capable of supporting many users and performs better in terms of achievable bit error rate (BER) in the context of DL communications with reduced number of antennas.

This paper proposes a finite-precision decoding method for low-density parity-check (LDPC) codes that features the three steps of Reconstruction, Computation, and Quantization (RCQ). Unlike Mutual-Information-Maximization Quantized Belief Propagation (MIM-QBP), RCQ can approximate either belief propagation or Min-Sum decoding. MIM-QBP decoders do not work well when the fraction of degree-2 variable nodes is large. However, sometimes a large fraction of degree-2 variable nodes is used to facilitate a fast encoding structure, as seen in the IEEE 802.11 standard and the DVB-S2 standard. In contrast to MIM-QBP, the proposed RCQ decoder may be applied to any off-the-shelf LDPC code, including those with a large fraction of degree-2 variable nodes. Simulations show that a 4-bit Min-Sum RCQ decoder delivers frame error rate (FER) performance within 0.1 dB of floating point belief propagation (BP) for the IEEE 802.11 standard LDPC code in the low SNR region. The RCQ decoder actually outperforms floating point BP and Min-Sum in the high SNR region were FER less than 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-5</sup> . This paper also introduces Hierarchical Dynamic Quantization (HDQ) to design the time-varying non-uniform quantizers required by RCQ decoders. HDQ is a low-complexity design technique that is slightly sub-optimal. Simulation results comparing HDQ and optimal quantization on the symmetric binary-input memoryless additive white Gaussian noise channel show a mutual information loss of less than 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-6</sup> bits, which is negligible in practice.

발광 다이오드와 같은 광원을 이용하여 조명과 통신의 두가지 기능을 동시에 이용할 수 있는 가시광 무선 통신은 최근 초고속 개인용 무선 네트워크에서 각광을 받고 있다. 광원의 제한된 대역폭으로 인하여 무선 광채널에서 전송률을 향상시키는 것이 이슈로 대두되는 가운데, 본 논문에서는 전송률을 향상시키는 기법으로써 다중 입출력 무선 광채널에서 두 개의 데이터 스트림을 지원하기 위해 고유값 분해를 이용한 공간 다중화 시스템을 설계한다. 채널의 변화에 따라 적응적 변조 기법을 적용하여 주파수 효율을 높이기 위해 펄스 진폭 변조 기법을 이용한다. 본 논문에서는 세기 변조를 이용한 변조 기법의 세 가지 제한 조건인 비음수성, 총 광출력값, 비트 오류율에 대하여 주파수 효율성을 향상시키기 위해 광출력값, 오프셋값, 변조 크기를 적응적으로 할당하기 위한 기법을 이론적으로 제안한다. 모의 실험 결과를 통해 본 논문의 제안 기법이 각 데이터 스트림에 광출력값을 동일하게 할당하는 기법에 비해 성능 향상을 이룰 수 있다는 것을 보인다. Visible light communication (VLC) using optical sources which can be simultaneously utilized for illumination and communication is currently an attractive option for wireless personal area network. Improving the data rate in optical wireless communication system is challenging due to the limited bandwidth of the optical sources. In this paper, we design the singular value decomposition (SVD)-based multiplexing multi-input multi-output (MIMO) system to support two data streams in optical wireless channels. In order to improve the spectral efficiency, the rate adaptation using multi-level pulse amplitude modulation (PAM) is applied according to the channel condition and we propose the method to allocate the optical power, the offset and the size of modulation scheme theoretically under the constraints of the nonnegativity of the modulated signals, the aggregate optical power and the bit error rate (BER) requirement. The simulation results show that the proposed allocation method gives the better performance than the method to allocate the optical power equally for each data stream.

Performance analysis of multicell multiuser MIMO MC DS/CDMA system with MMSE user-ordered SIC technique