Source/relays/destination combined MMSE-based optimization for AF-MIMO multiple-relay systems with correlated channel uncertainties

In this paper, source/relays-precoders and destination-equalizer combined optimization are proposed as a dual-hop amplify-and-forward (AF) multiple-input multiple-output (MIMO) multiple-relay system with Gaussian random and correlated channel uncertainties in both hops. Taking correlated channel uncertainties into account, a robust transceiver joint optimization design is developed based on the minimum mean-squared error (MMSE) criterion under individual power constraints at the source and the relays. Simulation results illustrate that the robust multiple relays/transceiver joint design architecture for an AF-MIMO system equipped with multiple relays substantially outperforms a nonrobust transceiver design that assumes estimated channels as actual channels.     

Performance of spatially multiplexed MC-CDM with zero-forcing unified successive interference cancellation detection

Spatially multiplexed multicarrier code-division multiplexing (SM-MC-CDM) is a multiple-input multiple-output, orthogonal frequency division multiplexing (MIMO-OFDM) communication technique with multiple antennas used for spatial multiplexing and with frequency domain spreading on each antenna. Unified successive interference canceller (U-SIC) is an efficient detector recently introduced for SM-MC-CDM. This paper presents an analytical approach to the performance of zero-forcing (ZF) U-SIC for SM-MC-CDM communications. For a system with an equal number of transmit and receive antennas, an approximation for the probability density function of post-detection signal-to-noise ratio (SNR) is used to derive a closed-form analytical upper bound and approximations for the probability of error and ergodic capacity. It is shown that SM-MC-CDM with ZF U-SIC is able to achieve higher diversity order than that achieved by ZF and minimum mean squared error (MMSE) V-BLAST detectors used on each subcarrier of a MIMO-OFDM system with the same number of subcarriers. The diversity order obtained increases with the number of subcarriers. It is also shown that the ergodic capacity of the system decreases with increasing number of subcarriers.     

Adaptive two-stage equalisation and FEXT cancellation architecture for 10GBASE-T system

For 10GBASE-T systems, variation in a multiple-input-multiple-output (MIMO) channel degrades the decision-point signal-to-noise ratio (DP-SNR) owing to imperfect pre-equalisation in the Tomlinson-Harashima precoding (THP) at the transmitter sides and catastrophic error propagation in far-end crosstalk (FEXT) cancellation at the receiver sides. Moreover, by using fixed THP coefficients during data transmission, as specified in the 10GBASE-T standard, and the non-linearity of THP pose challenges in the design of adaptive receivers. The authors propose an adaptive two-stage equalisation and FEXT cancellation (TS-EFC) architecture without updating the THP coefficients to combat channel variation at both the transmitter and receiver sides. In the first stage, we propose a new non-decision-directed FEXT canceller at the transmitter side using a joint training architecture to avoid error propagation. In the second stage, we devise an adaptive MIMO equaliser together with a novel pre-processing unit at the receiver side to combat channel variation. The pre-processing unit can eliminate the non-linearity issue by estimating both effective data sequences and precoded channel inputs. In addition, we develop a block least mean square algorithm that exploits the properties of two-dimensional modulated symbols for updating coefficients of the adaptive MIMO equaliser. Simulation results show that our TS-EFC architecture is robust against channel variation and significantly improves the DP-SNR. It eliminates the error propagation and also achieves faster convergence rates during the adaptation process.     

Multiuser scheduling in high speed downlink packet access

Multiuser scheduling is an important aspect in the performance optimisation of a wireless network as it allows multiple users to efficiently access a shared channel by exploiting multiuser diversity. For example, the 3GPP cellular standard supports multiuser scheduling in the high speed downlink packet access (HSDPA) feature. To perform efficient scheduling, channel state information (CSI) for users is required, and is obtained via their respective feedback channels. Multiuser scheduling is studied assuming the availability of perfect CSI, which would require a high bandwidth overhead. A more realistic imperfect CSI feedback in the form of a finite set of channel quality indicator values is assumed, as specified in the HSDPA standard. A global optimal approach and a simulated annealing (CSA) approach are used to solve the optimisation problem. Simulation results suggest that the performances of the two approaches are very close even though the complexity of the simulated annealing (SA) approach is much lower. The performance of a simple greedy approach is found to be significantly worse.     

Linear precoding for the downlink of multiple input single output coexisting wireless systems

Coexisting radio systems, often called cognitive radio (CR), have attracted much attention because of the lack of spectrum resources and the low usage statistics of existing spectrum allocations. Interference suppression and cancellation are seen as key technologies for enabling coexisting systems, and the application of multiple antennas might be one solution to tackle interference. Linear vector precoding for downlink of multiple input single output CR systems is addressed. The maximum ratio transmission, zero forcing, optimal interference-free, and optimal interference-constrained (IC) precoding algorithms in the sense of minimum mean squared error (MMSE) are presented. Then the authors compare and analyse these algorithms under different channel assumptions. The simulation results show that the proposed IC precoding algorithm can maximise the utilisation of multiple antennas and greatly improve the system performance.     

Optimal power and subcarriers allocation in downlink OFDMA system with imperfect channel knowledge

Most of existing work on resource allocation in TDMA and OFDMA systems assumes the availability of perfect channel state information (CSI) at the transmitter, which is rarely possible due to feedback delay and channel estimation error. In this paper, we study the effect of feedback delay and channel estimation error on margin adaptive resource allocation in a downlink OFDMA system. By using convex optimization framework, we find an optimal solution to the problem. First, we study the individual effect of feedback delay and channel estimation error on resource allocation by considering them exclusively. Then, we consider the simultaneous presence of feedback delay and channel estimation error and study their combined effect on resource allocation. We derive an explicit close form expression for the users’ transmit power and propose an algorithm for power and subcarriers allocation for each of these three scenarios. The algorithms have polynomial complexities and solve the problem with zero optimality gaps. Simulation results show that the system performance is very sensitive to feedback delay and is affected significantly by imperfect channel estimation. Our proposed algorithms highly improve the system performance in the availability of only imperfect CSI at the transmitter.     

Blind adaptive and iterative interference cancellation receiver structures based on the constant modulus criterion in multipath channels

Blind adaptive and iterative interference cancellation (IC) receiver structures for direct sequence code division multiple access systems in multipath channels are proposed. A code-constrained constant modulus design criterion based on constrained optimisation techniques and adaptive algorithms for receiver and channel parameter estimation are described for successive IC (SIC) and parallel IC (PIC) detectors and a new hybrid IC (HIC) scheme in scenarios subject to multipath fading. The proposed HIC structure combines the strengths of linear, SIC and PIC receivers and is shown to outperform the conventional linear, SIC and PIC structures. A novel iterative detection approach that generates different cancellation orders and selects the most likely symbol estimate on the basis of the instantaneous minimum constant modulus criterion is also proposed and combined with the new HIC structure to further enhance performance. Simulation results for an uplink scenario assess the algorithms, the proposed blind adaptive IC detectors against existing receivers and evaluate the effects of error propagation of the new cancellation techniques.     

Hybrid detectors for wireless orthogonal frequency division multiplexing with code division multiplexing systems based on reliability information

Orthogonal frequency division multiplexing with code division multiplexing (OFDM-CDM) is attractive for the next generation high-speed wireless systems due to the fact that the performance of OFDM-CDM systems can be considerably improved by employing a joint detection scheme such as the maximum likelihood (ML) detector. However, the complexity of the ML detector increases rapidly as the number of orthogonal spreading codes and/or the number of bits per modulation symbol increase. In this study, the authors introduce a unified detection model and propose two hybrid detectors, which combine zero forcing (ZF) with successive interference cancellation (SIC) and sphere detection (SD) algorithms, respectively. After obtaining the initial solution from the front-end ZF receiver, the proposed back-end algorithms are adopted to extend the potential solution list and search for the final result. The objective is to utilise the combination of a simplified linear equaliser and a comprehensive detection scheme to achieve enhanced performance and offer alternatives to the more complex and channel-estimation-sensitive minimum mean squared error (MMSE) scheme. The results show that the proposed hybrid detectors are able to achieve superior performance compared to the MMSE scheme and provides a significant performance improvement compared to the conventional OFDM counterpart.     

大规模MIMO系统的全导频RZF预编码方法

研究了大规模多输入多输出(MIMO)系统的预编码。针对小区间干扰和导频污染会对预编码的有效性产生较大影响的问题,提出了一种改进的全导频正则化迫零(RZF)预编码方法。该方法通过将有限的正交导频信号分配给小区用户来对预编码矩阵中的信道向量进行优化,得到优化后的全导频正则化预编码矩阵,并依此推导出新的包含导频污染函数和用户干扰函数的和速率表达式。另外,综合考虑基站天线数、用户数以及导频重用因子,优化其配置关系,从而用较少的用户信息和更高的导频重用因子来抑制更多的小区间干扰,有效地提升系统性能。实验结果表明,这种改进的RZF预编码算法能够较好地提高系统容量,在完全已知信道状态信息(CSI)和未完全已知CSI两种情况下的频谱效率及和速率均优于传统的RZF方法。     

Joint design of optimum partial response target and equalizer for recording channels with jitter noise

We address joint design of optimum generalized partial response (GPR) target and equalizer for perpendicular recording channels with jitter noise. We develop a new cost function which accounts for the data-dependent nature of jitter noise based on the minimum mean square error (MMSE) criterion. Using the step-response-based channel model, we derive expressions for the statistics required to compute the optimum equalizer and target in the presence of jitter noise. We also derive a bit-response-based model for the jitter noise channel. We present an approach for doing simulations as well as analytical computations for the jitter noise channel without resorting to the widely used Taylor series approximations. Our computational and simulation results show that, while the targets designed without accounting for the jitter lead to error-floor effect in the bit-error-rate performance, the targets designed by our approach give significant performance improvement under high jitter conditions, with no sign of error-floor effect for the range of signal-to-noise ratios considered.     

Error probability of direct sequence-code division multiple access systems with adaptive antenna minimum mean-square error multiuser receivers in Rayleigh-lognormal fading

In direct sequence-code division multiple access (DS-CDMA) cellular systems spreading codes, fading and positions of the users can be modelled as independent random variables and the corresponding multiuser interference (MUI) experienced by the base station is non-stationary. Here we evaluate in closed form the bit error probability for space-time linear minimum mean square error (MMSE) multiuser receivers for symbol-synchronous DS-CDMA system (bounds are provided for symbol-asynchronous system) by extending the known asymptotic results for random spreading sequences to non-stationary MUI. The analysis is based on the effective interference at the decision variable that is carried out to account for the non-stationary MUI that results from the multiuser beamforming that adapts each spatial filter to the randomness of the angle of arrivals of all the users. Propagation for each user is Rayleigh-lognormal faded channels as it is fairly general to model the imperfect power-control. The numerical validation proves that a simple geometrical model is accurate to evaluate the error probability for any arbitrary system loading.     

Decision-directed channel estimation based on iterative linear minimum mean square error for orthogonal frequency division multiplexing systems

A decision-directed (DD) channel estimation based on iterative linear minimum mean square error (LMMSE) is proposed for orthogonal frequency division multiplexing systems. Existing DD channel estimation is well known to have the problem of error propagation because of symbol-by-symbol detection. The proposed algorithm can estimate the correction term of current channel state information (CSI) according to the error vector of previous CSI by applying the orthogonality principle, and corrects the current CSI with this correction term. Analysis and simulation results have shown that this method has no error propagation problem. The performance of the proposed algorithm is much better than the conventional DD channel estimation, and close to the optimal LMMSE estimator, but with much less computational complexity compared with the optimal LMMSE estimator.     

Scenario-based approach for flexible resource loading under uncertainty

Order acceptance decisions in manufacture-to-order environments are often made based on incomplete or uncertain information. To quote reliable due dates in order processing, manage resource capacity adequately and take into account uncertainty, the paper presents and analyses models and tools for more robust resource loading. We refer to the problem as flexible resource loading under uncertainty. We propose a scenario-based solution approach that can deal with a wide range of uncertainty types. The approach is based on an MILP to find a plan with minimum expected costs over all relevant scenarios. To solve this MILP, we propose an exact branch-and-price algorithm. Further, we propose a much faster improvement heuristic based on an LP (linear programming) approximation. A disadvantage of the scenario-based MILP, is that a large number of scenarios may make the model intractable. We therefore propose an approximate approach that uses the aforementioned solution techniques and only a sample of all scenarios. Computational experiments show that, especially for instances with sufficient slack, solutions obtained with deterministic techniques that only use the expected scenario can be significantly improved with respect to their expected costs (i.e. robustness). We also show that for large instances, our heuristics outperform the exact approach given a maximum computation time as a stopping criterion. Moreover, it turns out that using a small sample of selected scenarios generally yields better results than using all scenarios.     

稳健的稀疏信号单快拍波达方向估计

通过稀疏重构得到传感器阵列输出数据的稀疏表示模型,研究了单快拍采样情形下的信号到达角(Direction of Arrival, DOA)估计问题。提出了一种基于最小均方误差(Minimum Mean-Square Error, MMSE)准则迭代实现的单快拍到达角估计算法(Iterative Implementation of MMSE, II-MMSE)。该算法将原有的稀疏表示模型中稀疏信号矢量的求解问题,转化为迭代求解稀疏功率对角阵,进而估计多目标信号的DOA。给出了算法的完整实现流程,从理论上分析了II-MMSE算法的迭代收敛性和对阵列模型误差的鲁棒性。仿真结果表明,II-MMSE算法在低信噪比、相干背景、小样本、阵列未校准等条件下都具有良好的测向精度和多目标分辨能力。     

Joint channel tracking and intercarrier-interference equalisation for vertical Bell Labs layered space time-orthogonal frequency division multiplexing in vehicle ad hoc network

Vertical Bell Labs layered space time-orthogonal frequency division multiplexing (VBLAST-OFDM) systems can achieve high spectral efficiency in quasi-stationary links and with channel state information (CSI) matrix knowledge. Owing to the high speeds of nodes in vehicle ad hoc network (VANET), the channel is fast fading thus raising the need for channel tracking. Furthermore, inter-carrier interference (ICI) causes an error floor at high signal-to-noise ratio (SNR) even with perfect CSI knowledge. In this paper we investigate channel tracking and ICI mitigation for VBLAST-OFDM. The analysis of ICI shows that it increases with speed, number of subcarriers and/or number of transmit antennas. The authors then introduce a simple channel tracking algorithm for VBLAST-OFDM. Simulation results show that our algorithm reduces the bit error rate (BER) of a 2 x 4 VBLAST system by 102² at 40 dB SNR and 100 km/h speed compared to obtaining a channel estimate from a training sequence only. The change in the channel response is estimated using the channel tracking algorithm and then passed to an ICI equaliser to enhance performance and reduce the error floor caused by ICI at high SNR. Equalising five pairs of subcarriers gives 4 dB improvement for 2 x 4 VBLAST at 180 km/h relative speed. The performance is enhanced as more subcarriers are included in the ICI equaliser at the expense of increased receiver complexity.     

Iterative soft-minimum mean-square error equalization for digital nonlinear page-oriented memories

Digital page-oriented volume holographic memory (POVHM) is a promising candidate for next-generation ultrahigh capacity optical data storage technology. As the capacity of the POVHMs increases, the bit error rate performance of the system is degraded due to increased interpixel interference (IPI) and noise. To improve the system performance under these adverse effects and to increase the capacity, joint iterative soft equalization-detection and error correction decoding might be attractive. To address that, by considering the nonlinearity inherent in the channel, an iterative soft equalization method that is optimized in the minimum mean-square error (MMSE) sense, called the iterative soft-MMSE (ISMMSE) equalization, is devised. The performance of the ISMMSE is evaluated by use of numerical experiments under different amounts of IPI and optical noise. Simulation results suggest that the ISMMSE is a good candidate for an ultrahigh capacity POVHM, which employs joint iterative equalization-detection and decoding.     

Optimisation of laminated cylindrical pressure vessels under strength criterion

An approach for the optimisation of symmetrically laminated cylindrical pressure vessels is presented. The analysis is based on the membrane theory of shells and the optimisation is carried out with respect to the fibre orientations and thickness distributions subject to the Tsai-Wu failure criterion. The approach is equally applicable to balanced and unbalanced symmetrically laminated shells. Two examples are considered which involve the design of cylindrical shells for maximum burst pressure and minimum weight. Numerical results are given for pressure vessels subject to internal pressure only and to a combination of internal pressure and liquid pressure. The effect of axial loading and torque on the designs is discussed.     

Effect of error in channel state information on the channel capacity with QAM signalling and the design of robust signal constellations

The effects of channel estimation errors on the channel capacity of a discrete time, discrete input, infinite output Rayleigh fading channel are investigated. The case of conventional modulation methods such as phase shift keying (PSK) and quatrature amplitude modulation (QAM) is investigated at first where it was observed that the capacity degrades rapidly with increasing channel estimation errors. The effect of error in the channel estimation is similar to the effect of higher noise in the channel that depends on the transmitted signal. A genetic algorithm is used to optimise the signal constellation in order to maximise the capacity for a given finite number of signal points. The aim of trying to maximise the capacity is to estimate the remaining gap in performance between a traditional modulation scheme such as QAM and the best possible constellation that is optimised for the channel. The constellations obtained from the genetic algorithm are, in general, not directly implementable. A method to design practical robust signal constellations that overcome the effect of channel state information (CSI) error is presented. The robust signal constellations obtained show a performance that is very close to the optimal constellations. In this work, the probability distribution of the error in CSI is assumed to be known.     

Approximate maximum likelihood serial decision-feedback equaliser and tomlinson?harashima pre-equalisation

Joint transmitter and receiver design problem for frequency-selective, time-invariant fading channels are studied. The authors first propose a simple approximate maximum likelihood serial decision-feedback equaliser (A-ML-SDFE) through DFE, a Gaussian approximation, a pre-whitening filter and a matched filter. Secondly, assuming full channel knowledge available at the transmitter side, the authors perform preequalisation in a downlink scenario by moving the decision-feedback part of the A-ML-SDFE to the transmitter. The proposed A-ML-SDFE achieves much better performance than linear minimum mean square error (MMSE) and MMSE-DFE with a lower complexity. The pre-equaliser further improves the system performance at low signal-to-noise ratio with a reduced receiver complexity.     

Integrated low-carbon distribution system for the demand side of a product distribution supply chain: a DoE-guided MOPSO optimiser-based solution approach

This article contributes to distribution system literature on three inter-linked aspects viz. formulation of a novel integrated low-carbon/green distribution system for the demand side of a Supply Chain (SC) with a single product and multiple consumers, i.e. drop-off points, a novel and robust solution approach through a Design of Experiment (DoE)-guided Multiple-Objective Particle Swarm Optimisation (MOPSO) optimiser and exhaustive analysis of the solutions (i.e. prioritisation, ranking and scenario analysis). The total costs, CO₂ emission and the traversed distances of the vehicles during transportation are optimised. The optimisation model for the strategic decision-making is formulated by effectively integrating the 0–1 mixed-integer programming with a green constraint based on Analytic Hierarchy Process. Due to the computationally NP-hard characteristic of the model, a systematic and technically robust DoE-guided solution approach is designed using a commercial solver – modeFRONTIER^®. DoE guides the solution through the MOPSO optimiser in order to eliminate the un-realistic set of feasible and optimal solution sets. A popular multi-attribute decision-making approach, TOPSIS, evaluates the solutions found from the Pareto optimal solution space of the solver. Finally, decision-makers’ preferences are analysed for monitoring the changes in the controlling parameters with respect to the changes in the decisions. A scenario analysis of the events by considering alternative possible outcomes is also conducted. It is found that the implemented methodology successfully routes the vehicles with optimal costs and low-carbon emission thus contributing to greening the environment on the demand side of a SC network.