Joint optimization of TCQ-TCM systems

Signal set expansion and set partitioning ideas from trellis coded modulation (TCM) have been previously applied to develop a source coding technique known as trellis coded quantization (TCQ). It has been also known that joint optimization of source and channel encoders/decoders results in substantial performance improvement. In this work, we investigate the performance of joint TCQ/TCM systems and develop various system optimization techniques. We consider channel optimized TCQ levels and asymmetric TCM symbol sets, and propose a simulated annealing based algorithm for joint optimization of TCQ levels and TCM symbols. Using these techniques signal to quantization noise ratio (SQNR) gains of 0.5-4 dB over nonoptimized systems are attained off-line. This, in turn, provides all the gain of going to a one step higher order trellis     

CDMA网络寻呼策略优化探讨

通过对移动用户和网络特性的分析,结合核心网和无线侧,研究了CDMA网络的寻呼类型,给出语音和短信寻呼的基本方法,LAC(location area code,位置区码)位置区设置和周期性位置更新的重要策略,并对网络寻呼与某些业务的触发先后次序、关键定时器之间的冲突以及寻呼与移动终端的配合等问题进行了研究,提出了能够提高系统接通率和改善用户感知的寻呼策略方法:增加二次或三次寻呼、LAC边界避开话务密集地区、同一LAC下的周期性位置更新参数设为一致、周期性位置更新定时器无线侧设为小于网络侧等。     

Joint optimization of data network design and facility selection

The authors describe a data network design model based on a mixed integer/linear programming (MILP) formulation that does not, as do most other approaches, separate link capacity and facility selection from routing and topological design; it fully integrates these processes to capture the important couplings that exist between them. The performance constraints are incorporated into the model in such a way that they are linear, but lead to the same grade of service for a balanced network as nonlinear average network delay constraints. It is shown that this formulation leads to a natural decomposition of the optimal design problem into two subproblems solvable sequentially. In the absence of capacity allocation constraints, the capacity and flow assignment problem is solved optimally and efficiently as part of the overall design process. Moreover, the model leads directly to the solution of multifacility design problems. A fast link reduction algorithm that efficiently designs single or multifacility networks and yields robust local extrema is presented. This algorithm is based on a special-purpose monotonic greedy drop heuristic procedure. An important application of this model is the design of multifacility networks     

MIMO多中继辅助通信中的优化调度

针对中继辅助通信系统,讨论了多中继并行传输下的优化设计问题,提出了一种简化的线性优化方案,并从多用户分集的角度,在等待服务用户中选择中继协作分集增益较大的用户对其进行服务.这种方案巧妙地减少了由于多中继并行传输所造成的用户间干扰,保持了多中继并行传输引入的空间分集所带来的性能优势,达到了提高系统总吞吐量的目的.     

Joint optimization of block size and quantization forquadtree-based motion estimation

A new approach to finding the best block size for quadtree-based motion estimation is developed and compared to a conventional fixed block size algorithm. The optimal balance between the motion vector bits and the discrete cosine transform (DCT) coefficient bits is achieved by a fast tree optimization technique based on Lagrange multiplier.     

Joint optimization of VQ codebooks and QAM signal constellationsfor AWGN channels

A joint design scheme has been proposed to optimize the source encoder and the modulation signal constellation based on the minimization of the end-to-end distortion including both the quantization error and channel distortion. The proposed scheme first optimizes the vector quantization (VQ) codebook for a fixed modulation signal set, and then the modulation signals for the fixed VQ codebook. These two steps are iteratively repeated until they reach a local optimum solution. It has been shown that the performance of the proposed system can be enhanced by employing a new efficient mapping scheme between codevectors and modulation signals. Simulation results show that a jointly optimized system based on the proposed algorithms outperforms the conventional system based on a conventional quadrature amplitude modulation signal set and the VQ codebook designed for a noiseless channel     

Joint optimization of FIR prefilter and channel estimate for sequence estimation

We provide simple analytical results for the coefficients of a finite-impulse response (FIR) prefilter and the effective channel impulse response (IR) for use in cellular communication systems. We show that using a FIR filter with both causal and anticausal filter taps, it is possible to find the jointly optimized impulse response, such that the signal-to-noise ratio is maximized in the least-squares sense. We show via computer simulation for 8-ary phase-shift keying in Enhanced Data rates for Global Evolution (EDGE) that the joint optimization of the prefilter and IR produces results similar to the minimum mean-square error decision-feedback equalizer prefilter in thermal noise, but yields gain in colored noise.     

频谱检测门限与n-out-of-K融合规则的联合优化

为了减少计算复杂度,提出联合优化检测门限λ和n-out-of-K融合规则的算法.以λ和n为参数建立目标函数,并将参数以二进制形式表示,从而把算法转化为组合优化问题.接着,采用基于样值修改的互熵优化方法渐次逼近最优的参数.仿真表明,该算法在获得与已有算法几乎相当的总错误率情况下,可有效降低平均搜索次数,且随着K的增加搜索次数增加更平缓.     

Joint optimization of power scheduling and rate-distortion performance in one-helper problem

We consider the many-help-one problem, also called m-helper problem, for the special case of m = 1 where one source provides partial side information to the fusion center (FC) to help reconstruction of the other correlated source. Both correlated sources communicate information about their observations to the FC through an orthogonal multiple access channel (MAC) without cooperating with each other. First, we characterize the optimal tradeoff between the transmission cost, that is, power, and the distortion D. Then, we consider a joint optimization of source coding and power scheduling from an information theory perspective, where the power scheduling is verified using Shannon capacity formula and the source-coding problem is analyzed using rate-distortion theory. We show that the joint optimization in the Gaussian one-helper problem can be solved analytically. We provide closed-form expressions for the optimal distortion and the optimal power scheduling in terms of the cost weights. Copyright © 2008 John Wiley & Sons, Ltd.     

认知无线网络中功率和信道接入的联合优化

在认知无线网络中,针对系统中所有用户能否接入同一信道进行通信的问题,提出了适用于不同情形的联合优化方案.在系统不可行的情形下,提出了联合优化功率和接入控制的方案.由于接入控制是NP问题,于是利用所提LP-PSO算法来实现优化控制,并分析和证明了所提算法的收敛性.在系统可行的情形下,提出了联合优化功率和传输速率分配的方案,通过改进拉格朗日对偶(Lagrange duality)算法来实现优化控制.数值结果分析表明,相比其他接入控制算法,虽然所提算法的时间复杂度有所增加但能够快速收敛,在有效地提高接入量的同时还能降低功率消耗,并能使传输速率得到更公平的分配.     

Joint optimization of energy harvesting and information transmission for trapped user

Wireless Networks - Energy harvesting technology can solve the problem of users’ energy consumption in disaster areas. When disasters occur, some users are trapped and unable to recharge and...     

一种基于免疫的抗体优化策略及应用

受自然免疫系统相关机理的启发,本文提出了一种引入进化梯度的免疫遗传算法(EG-IGA)并应用于抗体的优化。该算法基本思想是将生成的多样性抗体,分成若干个小生境,并排挤掉同一个小生境中的较差抗体,保留优良抗体;然后执行GA交叉、变异等操作:再利用进化梯度为优良抗体标记进化方向,按标记的进化方向继续局部寻优,以较快的速度寻找最优的抗体种群。最后将EG-IGA算法和NGA算法分别运用在同一个多峰值函数上,实验结果表明,本文所提出的EG-IGA算法具有提高解的精度及收敛速度、找到更多最优解等特点。     

Joint QoS-control and handover optimization in backhaul aware SDN-based LTE networks

Future cellular networks will be dense and require key traffic management technologies for fine-grained network control. The problem gets more complicated in the presence of different network segments with bottleneck links limiting the desired quality of service (QoS) delivery to the last mile user. In this work, we first design a framework for software-defined cellular networks and then propose new mechanisms for management of QoS and non-QoS users traffic considering both access and backhaul networks, jointly. The overall SDN-LTE system and related approaches are developed and tested using network simulator in different network environments. Especially, when the users are non-uniformly distributed, the results shows that compared to other approaches, the proposed load distribution algorithm enables at least 6% and 23% increase in the average QoS user downlink throughput and the aggregate throughput of 40% users with lowest throughput (edge users), respectively. Also, the proposed system efficiently achieves desired QoS and handles the network congestion without incurring significant overhead.

     

Joint optimization of energy allocation and routing problems in wireless sensor networks

Energy allocation problems and routing problems are both important research issues in the wireless sensor network (WSN) field. The former usually aims at considering how to allocate a certain number of sensor devices in a sensing region to form a WSN so that the objective function value (e.g., the network connectivity or the network lifetime) of the constructed network is optimized. For the message routing problem in WSNs, researchers tend to consider how to find an energy conservable message transmission routing scheme for notifying the supervisor of the WSN when an event occurs. Till now, many solutions have been proposed for the above two categories of optimization problems. However, unifying the above two network optimization problems to maximize the network lifetime, to the best of our knowledge, still lacks related research. This paper considers a joint optimization problem for energy allocation and energy‐aware routing called the joint optimization of energy allocation and routing problem (JOEARP) for a hierarchical cluster‐based WSN. We propose an exact algorithm to provide the optimum solution for the JOEARP. The simulation results show that this solution performed better in prolonging the network lifetime of a WSN in a real situation, compared to other compositions of conventional energy allocation schemes with some known routing algorithms. Copyright © 2009 John Wiley & Sons, Ltd.     

Joint optimization of spectrum access and power allocation in uplink OFDMA CR-VANETs

Wireless Networks - Cognitive radio (CR) is a state-of-the-art technology to solve the spectrum shortage problem for emerging wireless services, which include the CR-enabled vehicular ad hoc...     

Joint optimization of relay strategies and resource allocations in cooperative cellular networks

This paper considers a wireless cooperative cellular data network with a base station and many subscribers in which the subscribers have the ability to relay information for each other to improve the overall network performance. For a wireless network operating in a frequency-selective slow-fading environment, the choices of relay node, relay strategy, and the allocation of power and bandwidth for each user are important design parameters. The design challenge is compounded further by the need to take user traffic demands into consideration. This paper proposes a centralized utility maximization framework for such a network. We show that for a cellular system employing orthogonal frequency-division multiple-access (OFDMA), the optimization of physical-layer transmission strategies can be done efficiently by introducing a set of pricing variables as weighting factors. The proposed solution incorporates both user traffic demands and the physical channel realizations in a cross-layer design that not only allocates power and bandwidth optimally for each user, but also selects the best relay node and best relay strategy (i.e. decode-and-forward vs. amplify-and-forward) for each source-destination pair     

Joint transmitter-receiver optimization in synchronous multiusercommunications over multipath channels

Transmitter optimization, in addition to receiver optimization, contributes significantly to efficient interference suppression in multiple access and multipath channels. The system design is based on the joint optimization of the transmitter and the receiver in a synchronous multiuser channel characterized by multipath propagation. Joint optimization is represented by a linear transformation of the transmitted signals at the transmitter and a linear transformation of received signals at each receiving site that minimize the effect of multiple access and multipath interference. The minimum mean squared error between the true bit value and its estimate at the output of the receiver is taken as the cost function, subject to average and peak transmit power constraints. It is shown that joint transmitter-receiver optimization outperforms significantly either transmitter optimization or receiver-based techniques. The crucial assumption, in the case of multipath channels, is that the transmitter knows the multipath characteristics of all channels and that the channel dynamics are sufficiently slow so that multipath profiles remain essentially constant over a block of preceded bits. The practical applications can be found in indoor and cellular communications, satellite communications, or military communications where nonorthogonal signature waveforms are employed     

Joint transmitter-receiver optimization for multi-inputmulti-output systems with decision feedback

The joint transmit-receive optimization problem for multiuser communication systems with decision feedback is investigated. It is shown that minimization of the geometric mean-squared error (defined as the determinant of the error covariance matrix) leads to a tractable transmitter optimization problem for general multi-input multi-output decision-feedback systems. Several computational results are included that highlight system performance for a variety of useful transmission scenarios     

异构蜂窝网络中用户关联与基站功率的协同优化

为实现异构蜂窝网络中宏基站和小基站之间的负载均衡,提出了一种基于效用函数最大化模型的用户关联机制和基站功率控制的协同优化方案.通过迭代算法求解该协同优化问题,首先在基站功率固定的情况下求得最佳用户关联策略,然后在所得的用户关联策略基础上通过Zoutendijk可行方向法求得基站最佳功率.通过协同优化获得的用户关联策略和基站功率控制实现了基站之间的负载均衡,通过降低宏基站功率和关闭闲置小基站降低了基站的能耗.仿真实验表明,所提方案和不实施功率控制的用户关联策略相比,实现了宏基站与小基站之间的负载均衡,降低了宏基站对小基站用户的干扰,提升了小基站用户的信号干扰噪声比,用户速率中位值提高了20％.