In this special issue, we cover some recent results in the following four emerging areas: 5G cellular systems, big data systems, bio/nano/molecular networks, and smart grids. In the past several years, there are various technologies emerging, which are either directly or indirectly related to communication. Some of them are over the evolution of traditional communication systems, while others are over new systems such as smart grids, molecular networks, and big data systems.

In this paper, we are interested in blind and semi-blind identification of multiple-input multiple-output (MIMO) channel for orthogonal frequency division multiplexing (OFDM) systems. Using the sparsity property of wireless channel impulse response, we propose an iterative method which minimizes a cost function to result from the combination of blind or semi-blind criterion and the lp norm. This norm is considered as a good sparsity measure. The simulations show that the proposed method outperforms existing techniques in terms of estimation error and robustness to channel order overestimation.

This paper describes design methods of multiuser MIMO (multiple input multiple output) AF (amplify and forward) relay system. Assuming the application to multi-cellular systems, the cancellation of interuser interference is considered both in the first and second hops under perfect knowledge of CSI (channel state information). First, a maximal SINR (signal to interference plus noise ratio) approach using iterative optimization is given. Then a partial ZF (zero forcing) based method which cancels all the interferences not only in one side of transmitter or receiver, but by cooperative work of source-relay and/or relay-destination is considered both for nonseparable and separable relay weight matrices. By this operation, the restriction on the antenna number required for ZF could be released. Through computer simulations, the effectiveness of the proposed method is demonstrated.

This paper presents a subband adaptive array (SBAA) with reduced pilot signal based on maximal ratio combining (MRC) scheme. By the subband processing, MRC design based on eigenfiltering which is widely used in frequency flat environments could be applied to frequency selective channels, but the efficient synthesis of output signal through the inverse DFT (discrete Fourier transform) is disturbed by the nonuniqueness of eigenvectors. In the proposed method, a two-step approach is adopted to solve this problem: in the first step, we use simple compensation of weight uncertainty with short (or possibly no) pilot signal and derive a hard-decision temporary output. Then in the second step, the output data is used as a training sequence to determine optimum compensation. It is shown through computer simulations that the proposed scheme improves the transmission rate of SBAA scheme keeping good performance, and some fundamental features are also investigated.

In this paper, a novel HARQ scheme is proposed by grouping the information bit portion from failed packet and the new information bit portion from new transmit packet, and then both portions are encoded by CRC and turbo code. In the reception, both bit portions are jointly decoded to obtain grouped HARQ coding gain. System level simulation demonstrates that grouping based HARQ achieves 15% sector throughput gain as opposed to conventional Chase-combining HARQ by slightly suffering transmit latency and only adding an ACK/NAK bit.

In this paper, we investigate the system performance on decode and forward based bi-directional relaying based on symbol-wise XOR operation. This technique gives more freedom of selecting modulation and coding scheme at relay station, and significantly relaxes its transmission bottom neck. However, the performance degradation occurs when the modulation orders of both links differ from each other. To mitigate such an impact, we exploit a repetition coding scheme in conjunction with a redundant modulation code scheme by overlapping MCS levels. To this end, a system level simulation proves that the proposed scheme achieves about 40% capacity gain over bit-wise XOR based bi-directional relaying and gives additional 7% gain over symbol-wise XOR based bi-directional relaying.

This paper addresses time-domain channel estimation for pilot-symbol-aided orthogonal frequency division multiplexing (OFDM) systems. By using a cyclic sine-function matrix uniquely determined by N/sub c/ transmitted subcarriers, the performance of our proposed scheme approaches perfect channel state information (CSI), within a maximum of 0.4-dB degradation, regardless of the delay spread of the channel, Doppler frequency, and subcarrier modulation. In addition, reducing the matrix size by splitting the dispersive channel impulse response into clusters means that the degenerated inverse matrix estimator (DIME) is feasible for broadband, high-quality OFDM transmission systems. Computer simulations over realistic non-sample spaced channels also showed that the DIME is robust for inter-symbol interference (ISI) channels and fast time-invariant channels where a minimum mean squared error (MMSE) estimator does not work well.

This paper presents an implementation architecture based on per flow queueing that is capable of achieving QoS provisioning for future integrated services networks consisting of the guaranteed service (GS), the controlled-load (CL), and the best-effort (BE) service classes. We propose several novel traffic management mechanisms, including adaptive rate allocation for controlled-load (ARC), a hybrid model-based and measurement-based admission control algorithm for GS and CL flows, and a quasi-pushout plus (QPO+) packet discarding mechanism. Simulation results show that our architecture and algorithms provide hard QoS guarantees to GS flows under all conditions, consistent (soft) QoS to CL flows under both light and heavy load conditions, and effective control of negative impact from non-conforming CL flows. Our architecture and algorithms also resolve several issues associated with the traditional class-based approach.

Conventionally, the network layer (such as IP) to link layer (such as Ethernet and ATM) address translation is done in the link layer. This approach requires link technology-specific solutions such as ARP for Ethernet, and ATMARP or NHRP for ATM. By moving the address resolution function from link layer to network layer, this paper proposes a unified address resolution scheme applicable to current and future network technologies. For NBMA (non-broadcast multi-access) networks, this scheme achieves better implementation efficiency because the conventional scheme would require extra table lookups when the link layer has to consult with network-layer routing function to forward a request that cannot be resolved locally.

The authors present a structured codebook for reducing the complexity and memory of a CELP stochastic codebook search. The tree-structured delta codebook, whose code vectors are generated from a small number of delta vectors, can be searched efficiently by calculating the vector correlations recursively. The complexity was reduced to 1/70 that of a conventional full-Gaussian codebook, and the memory for codebook storage was reduced to 1/100. Another excellent feature of this codebook is the feasibility of changing the distribution of code vectors adaptively. The codebook adaptation method (delta vector sorting) provides an SNRseg improvement of 0.6 dB, and consistent improvement in perceptual quality, by changing the order of delta vectors to fit the input speech.>

The authors propose an algorithm in which multi-mode coding is a transparent adaptation of multi-stage VXC (vector excitation coding) requiring almost zero additional computation. In the process, it is shown how the cost of the jointly optimized multi-stage VXC can be minimized using a backward-transform implementation of the perceptually orthogonal VXC (POVXC) algorithm previously proposed by the authors. It is shown that the performance of such a coder, while not as good as that of a normal multi-mode coder, is noticeably better than that of a normal POVXC.>

The authors introduce two techniques for improving low-bit-rate CELP (code excited linear prediction) speech coders. The sparse-delta stochastic codebook is a recursive codebook design which can be searched using roughly 5% of the computational load required to search a full Gaussian codebook. Pitch sharpening is a class of algorithms which attempt to improve the perceptual quality of CELP by limiting the feedback of low-amplitude noiselike information to the adaptive codebook. Simulation results are presented for sparse-delta, ternary sparse-delta, and simplified-search sparse-delta coders, and for reduced-gain and sparse-adaptive-codebook pitch sharpening algorithms.>

A multimode source/channel coder which can dynamically control the balance of source and channel coding according to the channel quality is introduced. As an example of such a system, a 4.8-kb/s code excited linear predictive coder with three coding modes (A, B1, and B2), each of which has different bit assignments to source and channel coding, is presented. The optimum coding mode is selected in each frame, based on an evaluation of the spectral distortion (SN/sub LAR/) in reproduced speech. The threshold value of SN/sub LAR/ for mode decision is varied according to the channel error rate. Computer simulation shows that 2 dB and 3 dB of SNR/sub seg/ improvement is achieved at a bit error rate of 3*10/sup -3/ and 3*10/sup -2/ respectively, over conventional CELP without channel coding.>

Principal axis extracting vector excitation coding (PAVXC) is proposed in which an efficient codebook search method and an improved excitation modeling technique are used. A two-step codebook search using a small-size codebook of 20 dimensions (half the conventional size) can reduce the computational complexity by a factor of 64, maintaining the reproduced speech quality within a slight degradation of 0.9 dB in SNR seg. Multiple vector excitation using an impulse vector jointly with the conventional stochastic code vector can provide more precise representation of the excitation. The impulse vector is extracted from each code vector by principal axis extraction, and its gain is jointly optimized with the gain for the code vector. The improvement in SNR seg is 1.2 dB, which compensates for the degradation caused by the two-step codebook search. The quality of the reproduced speech using PAVXC is subjectively much better than that of conventional VXC, thanks especially to the improvement in voiced regions.>

The authors introduce a novel approach to narrow- and medium-band speech coding that can dynamically balance the transmission rate between the excitation and the spectral parameters. The coding algorithm, called multimode coding, operates several coding blocks, each of which has a different bit assignment in parallel, and selects the optimum coding block frame by frame based on an evaluation of the reproduced speech quality. This coding algorithm is applied to 4.8 and 8.0 kb/s CELP coders, and 2.0-2.4 dB of SNRseg improvement is achieved over conventional CELP coders. The spectral distortion measure is added as an evaluation function, improving the subjective speech quality.>

A speech coding algorithm with low complexity and a short processing delay is introduced. The proposed algorithm is ADPCM (adaptive digital pulse code modulation) with a multiquantizer (ADPCM-MQ). The input signal is processed in parallel by multiple ADPCM coders with different characteristics. Then the optimum ADPCM coder with minimum error power is dynamically selected for each frame. A 16-kb/s codec based on this algorithm has been implemented using two general-purpose digital signal processors (MB8764) with 8.3 ms of total processing delay. A segmental SNR of 19-21 dB was achieved at 16 kb/s; with postfiltering the segmental SNR was increased to 23-25 dB. Combined with the time domain compression scheme, the algorithm can be easily applied to 8-kb/s coding. It is also extensible to variable-rate coding.>

This paper describes an implementation of a new 16 kbps speech codec using commercially available DSPs and its performance. The coding algorithm chosen here is ADPCM with Multi-Quantizer (ADPCM-MQ) which selects the optimum ADPCM coder frame by frame and switches to it dynamically. To implement this coding algorithm, we used two Fujitsu DSPs (MB8764), 1.5 chips for the encoder and 0.5 chip for the decoder. Reconstructed speech with a 21 dB segmental SNR was obtained. With error correction, this codec provides good speech quality even with a bit-error rate of 10^-2 to 10^-3. To improve the subjective quality of the reconstructed speech, adaptive postfiltering was also applied. Since the processing delay of this codec is less than 10 ms, no echo-canceller is needed. Moreover, 2400 bps voice band data (CCITT Rec.V. 26) could be transmitted with a data error rate from 10^-7 to 5×10^-6, and G.III facsimiles were successfully transmitted using this codec.

Adaptive differential PCM (ADPCM) is an effective coding scheme to simplify the hardware and shorten the processing delay to realize a high-efficiency speech codec. The ADPCM with Multi-Quantizer (ADPCM-MQ) coding has been proposed as one of the highly efficient coding methods. In the ADPCM-MQ codec several ADPCM coding blocks with different quantization step-size update rates are operated in parallel, and the quantizer that gives the best characteristics is found and selected dynamically for each frame. This paper describes a new 8 to 9.6 kbps ADPCM-MQ coding algorithm that includes tree coding to improve the per-sample quantizing characteristic, and sub-band coding with high frequency band reconstruction to realize a lower bit rate coding. Computer simulation indicates good quality for speech reproduced by this algorithm with a segmental signal-to-noise ratio of 14 to 15 dB. Adaptive postfiltering can be added to enhance the subjective characteristics of the reproduced speech.

Recently much intensive research of 16kbps Speech coding algorithm has been conducted aiming to reduce the transmission bit rate and yet provides high speech quality. Adaptive predictive coding with adaptive bit allocation (APC-AB)[1] is considered to be one promising approach. However, the processing of this coding algorithm is so complicated that the implementation of the algorithm on a general-purpose signal processor, especially if fixed-point arithmetic DSPs are used, requires careful study of arithmetic operation precision and same way to reduce the number of processing cycles. Taking account of these points, real-time signal processing using a fixed-point signal processing chip (FDSP-3) has been studied, and a prototype codec has been realized. The prototype codec satisfied the CCITT mask of signal-to-total distortion ratio for PCM codecs and showed quality good enough for "toll" speech.