High Rate Robust Codes with Low Implementation Complexity

In this paper, we present a low-complexity low data rate (LDR) ultra wideband (UWB) transceiver prototype CMOS chip suitable for a differential binary phase shift keying (DBPSK) modulation applied data transmission with 500 MHz-bandwidth signals. This solution, which is mainly based on "1.5-bit" direct sub-sampling at 1 Gsps and differential digital correlations, enjoys good immunity to clock drift and interferers. It is also likely to offer an interesting trade-off between fine performance in dense multipath environments, low implementation complexity, and hence low power consumption. At first, the 1.5 bits concept is discussed. Then, the implementation choices for some critical blocks of the RX data path are discussed to justify the adopted low-complexity approach. Finally, some preliminary implementation results are provided.

Postfilters for suppressing coding noises in low bit rate speech coders usually operate in the time domain with high complexity and also introduce nonlinear phase distortion to the speech signals because they are recursive filters. In this paper, a frequency-domain postfiltering technique for multiband excited linear predictive (MBELP) coders is proposed. The idea is to firstly sample the postfilter magnitude spectrum at the pitch harmonics and then scale the signal band magnitudes by the sampled postfilter magnitudes. This approach does not need to specifically perform the filtering process, and the signal energies before and after postfiltering can be easily equalized by simply re-scaling the signal band magnitudes. Another obvious advantage of using this frequency-domain postfiltering technique is that the phase information utilized in multiband synthesis will be retained because only the magnitude spectra are modified. In this paper, a fast method is given to sample the postfilter magnitude spectrum which is characterized by line spectral pair (LSP) parameters. The proposed frequency-domain postfilter has a much lower implementation complexity than its time-domain counterpart.

This paper presents the architecture design of a high-speed, low-complexity 128-point radix-2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">4</sup> FFT processor for ultra-wideband (UWB) systems. The proposed high-speed, low-complexity FFT architecture can provide a higher throughput rate and low hardware complexity by using 2-parallel data-path scheme and single-path delay-feedback (SDF) structure. This paper presents the key ideas applied to the design of high-speed, low-complexity FFT processor, especially that for achieving high throughput rate and reducing hardware complexity. The proposed FFT processor has been designed and implemented with the 0.18-mum CMOS technology in a supply voltage of 1.8 V. The throughput rate of proposed FFT processor is up to 1 Gsample/s while it requires much smaller hardware complexity

본 논문에서는 고해상도 영상의 효과적인 처리를 위한 블록 버퍼 기반의 저 복잡도 무손실 프레임 메모리 (frame memory) 압축 방법을 제안한다. 제안하는 압축 방법은 공간적 상관도를 제거하기 위하여 블록단위 MHT (modified Hadamard transform)를 사용하고, 엔트로피 부호화를 위하여 AGR (adaptive Golomb-Rice) 부호화 기법을 적용하여 저 복잡도 무손실 압축 및 효과적인 하드웨어 구현을 달성한다. MHT는 가산기와 1비트 오른쪽 시프트(1-bit right shift) 연산만으로 구성되어 있고, AGR은 별도의 메모리 공간 및 메모리 접근 동작(memory access operation)을 포함하지 않아 저 복잡도 구현이 용이하다. 기존의 저 복잡도 무손실 압축 방법과 비교하여 제안한 알고리즘은 압축률 측면에서 우수한 성능을 나타내고, 기존 코덱(codec)의 구조를 크게 수정하지 않으면서 화질의 열화없이 하드웨어 장치에 적용될 수 있음을 다양한 영상에 대한 실험 및 복잡도 분석을 통해 보인다. 또한 제안한 방법은 메모리 접근 동작을 필요로 하지 않아 하드웨어 구현을 위한 비용을 최소화 할 수 있어, Fill HD급 이상의 고해상도 영상을 효과적으로 처리하는데 유용하다. This study addresses a low complexity and lossless frame memory compression algorithm based on block-buffer structure for efficient high resolution video processing. Our study utilizes the block-based MHT (modified Hadamard transform) for spatial decorrelation and AGR (adaptive Golomb-Rice) coding as an entropy encoding stage to achieve lossless image compression with low complexity and efficient hardware implementation. The MHT contains only adders and 1-bit shift operators. As a result of AGR not requiring additional memory space and memory access operations, AGR is effective for low complexity development. Comprehensive experiments and computational complexity analysis demonstrate that the proposed algorithm accomplishes superior compression performance relative to existing methods, and can be applied to hardware devices without image quality degradation as well as negligible modification of the existing codec structure. Moreover, the proposed method does not require the memory access operation, and thus it can reduce costs for hardware implementation and can be useful for processing high resolution video over Full HD.

In this paper, we propose a DDoS defense architecture, named NEIF (Network Egress and Ingress Filtering), which is deployed at the Internet Service Provider's (ISP) edge routers to prohibit DDoS attacks into and from the ISPs' networks. The main challenge is how to implement NEIF with a small fixed amount of memory and low implementation complexity so that it may be acceptable by ISPs. We first design a bloom filter based data structure to identify and measure a few relatively large flows instead of all flows, where the amount of required memory is independent of link speeds and the number of flows. Then, the relatively large flows are rate-limited to their fair share based on the packet symmetry-the ratio of received and transmitted packets of a host. The dropping decisions of each flow are made on the observed counters directly that are with low implementation complexity. Finally, we implement NEIF with Click and perform experiments on PlanetLab. The experimental results validate our analysis and show that the Internet can benefit from NEIF even under partial deployment.

The achievable performance of channel coded space-time trellis (STT) codes and space-time block (STB) codes transmitted over wideband channels is studied in the context of schemes having an effective throughput of 2 bits/symbol (BPS) and 3 BPS. At high implementational complexities, the best performance was typically provided by Alamouti's unity-rate G/sub 2/ code in both the 2-BPS and 3-BPS scenarios. However, if a low complexity implementation is sought, the 3-BPS 8PSK space-time trellis code outperforms the G/sub 2/ code. The G/sub 2/ space-time block code is also combined with symbol-by-symbol adaptive orthogonal frequency division multiplex (AOFDM) modems and turbo convolutional channel codecs for enhancing the system's performance. It was concluded that upon exploiting the diversity effect of the G/sub 2/ space-time block code, the channel-induced fading effects are mitigated, and therefore, the benefits of adaptive modulation erode. In other words, once the time- and frequency-domain fades of the wideband channel have been counteracted by the diversity-aided G/sub 2/ code, the benefits of adaptive modulation erode, and hence, it is sufficient to employ fixed-mode modems. Therefore, the low-complexity approach of mitigating the effects of fading can be viewed as employing a single-transmitter, single-receiver-based AOFDM modem. By contrast, it is sufficient to employ fixed-mode OFDM modems when the added complexity of a two-transmitter G/sub 2/ scheme is affordable.

Maximum likelihood (ML) data aided channel estimation for wavelet packets based ultra wideband (WP-UWB) transmissions is investigated. Training pilot symbols are employed for ML channel estimation based on a least square algorithm derived from the optimum ML approach. An optimum training sequences criterion is derived. Based on this, nearly optimum perfect root of unity sequences (PRUS) are tested and compared to Gold sequences and random sequences. In this estimation strategy, a generalized inverse of the training pilot symbols matrix can be pre-computed and stored in memory. Furthermore, PRUS allows to save the inverse matrix operation and so reducing the complexity of the ML estimator significantly. This technique is especially attractive for low data rate transmissions as in sensor networks because of its low complex implementation. Performance analysis results in terms of the MSE are provided. Tradeoffs between performance and complexity are described as well. The investigated channel estimation algorithms for UWB channels offer flexibility, low complexity and robustness, making channel estimation fairly simple and effective

In massive multiple-input multiple-output (M-MIMO) systems, a detector based on maximum likelihood (ML) algorithm attains optimum performance, but it exhaustively searches all possible solutions, hence, it has a very high complexity and realization is denied. Linear detectors are an alternative solution because of low complexity and simplicity in implementation. Unfortunately, they culminate in a matrix inversion that increases the computational complexity in high loaded systems. Therefore, several iterative methods have been proposed to approximate or avoid the matrix inversion, such as the Neuamnn series (NS), Newton iterations (NI), successive overrelaxation (SOR), Gauss–Siedel (GS), Jacobi (JA), and Richardson (RI) methods. However, a detector based on iterative methods requires a pre-processing and initialization where good initialization impresses the convergence, the performance, and the complexity. Most of the existing iterative linear detectors are using a diagonal matrix ( D ) in initialization because the equalization matrix is almost diagonal. This paper studies the impact of utilizing a stair matrix ( S ) instead of D in initializing the linear M-MIMO uplink (UL) detector. A comparison between iterative linear M-MIMO UL detectors with D and S is presented in performance and computational complexity. Numerical Results show that utilization of S achieves the target performance within few iterations, and, hence, the computational complexity is reduced. A detector based on the GS and S achieved a satisfactory bit-error-rate (BER) with the lowest complexity.

Forensic watermarking is used in large-scale video-distribution applications to track digital pirates after they illegally leak videos. Existing methods either have a high embedding complexity or have troubles providing imperceptibility and robustness. Therefore, this paper proposes a novel watermarking method that has a low embedding complexity, as well as sufficient imperceptibility and robustness. The main novelty is that frames are replaced out of the loop, which has a very low complexity. This is inspired by A/B watermarking, yet applied on frame level rather than video-segment level. The resulting drift-error artifacts are used for robust watermark detection. Additionally, a faster watermark detection method is proposed at the cost of a decrease in embedding capacity. We show that the drift errors caused by frame replacement are imperceptible, and that our method has a negligible impact on the video bitrate. Moreover, we demonstrate a high level of robustness. These interesting properties come at the cost of a non-blind detection with a relatively high complexity, that is partially solved by the proposed fast detection method. Additionally, a high detection complexity is not necessarily a problem since detection occurs infrequently and recent speed-up solutions exist. In conclusion, the proposed method is a novel and scalable solution that enables secure large-scale video distribution.

Low complexity reconfigurable channelizers using non-uniform filter banks

A novel design and implementation technique for low complexity variable digital filters using multi-objective artificial bee colony optimization and a minimal spanning tree approach

A low complexity digital hearing aid is designed using a set of subband filters, for various audiograms. It is important for the device to be made of simple hardware, so that the device becomes less bulky. Hence, a low complexity design of reconfigurable filter is proposed in this paper. The tunable filter structure is designed using Farrow based variable bandwidth filter. The coefficients of the filter are expressed in canonic signed digit format. The performance can be enhanced using optimization algorithm. Here, we have explored the strength of hybrid evolutionary algorithms and compared their various combinations to select a proper coefficient representation for the Farrow based filter, which results in low complexity implementation.

In input-queued scheduling, iSLIP algorithm is a milestone for its high throughput and low implementation complexity. However under bursty arrivals, its average input latency increases dramatically and quite a few cells will be dropped as the input buffer overflows. Motivated by cutting down the cell loss rate without increasing average input latency, we present a new scheduling algorithm called iTFF (iterative time to leave and full or not first), which has better performance than iSLIP under bursty traffic conditions. Simulation results indicate that iTFF restrains the cell loss rate significantly and yet maintains low average input latency. Moreover, iTFF can be implemented in hardware to achieve high speed.

We consider the problem of implementing general shared-memory objects on top of write-once bits, which can be changed from 0 to 1 but not back again. In a sequential setting, write-once memory (WOM) codes have been developed that allow simulating memory that support multiple writes, even of large values, setting an average of \(1+o(1)\) write-once bits per write. We show that similar space efficiencies can be obtained in a concurrent setting, though at the cost of high time complexity and fixed bound on the number of write operations. As an alternative, we give an implementation that permits unboundedly many writes and has much better amortized time complexity, but at the cost of unbounded space complexity. Whether one can obtain both low time complexity and low space complexity in the same implementation remains open.

A comprehensive review of state of charge estimation in lithium-ion batteries used in electric vehicles