Blind adaptive MIMO receivers for space-time block-coded DS-CDMA systems in multipath channels using the constant modulus criterion

We propose blind adaptive multi-input multi-output (MIMO) linear receivers for DS-CDMA systems using multiple transmit antennas and space-time block codes (STBC) in multipath channels. A space-time code-constrained constant modulus (CCM) design criterion based on constrained optimization techniques is considered and recursive least squares (RLS) adaptive algorithms are developed for estimating the parameters of the linear receivers. A blind space-time channel estimation method for MIMO DS-CDMA systems with STBC based on a subspace approach is also proposed along with an efficient RLS algorithm. Simulations for a downlink scenario assess the proposed algorithms in several situations against existing methods.     

Blind adaptive code-constrained constant modulus algorithms for CDMA interference suppression in multipath channels

A code-constrained constant modulus (CCM) design criterion for linear receivers is investigated for direct sequence code division multiple access (DS-CDMA) in multipath channels based on constrained optimization techniques. A computationally efficient recursive least squares (RLS) type algorithm for jointly estimating the parameters of the channel and the receiver is developed in order to suppress multiaccess (MAI) and inter-symbol interference (ISI). An analysis of the method examines its convergence properties and simulations under nonstationary environments show that the novel algorithms outperform existent techniques.     

多天线系统中多中继传输的时间分配和功率分配优化方法

本文考虑单小区内的两个中继使用解码转发的方法为两个用户提供下行数据的场景,基站和中继配置多根天线,用户配置单天线。两中继使用相同的频率资源同时为两个用户提供服务。为减小两中继同时向两用户传输时产生的干扰,中继到用户的传输采用协作干扰避免的策略;相应的基站到中继的传输采用多用户空分复用的传输策略。本文在时间分配和功率分配两个方面对上述两跳传输过程进行了优化,提出了两跳传输最优的时间分配策略。由于功率分配最优化问题难以求解,本文提出了一种匹配链路容量的次优功率分配方法,并对其进行简化以降低复杂度。通过仿真可以看出,简化的功率分配方法与匹配链路容量的功率分配性能很接近;所提出的时间分配和功率分配方案可以获得有效的性能提升。      

Simultaneous suppression of multiaccess and narrow-bandinterference in asynchronous CDMA networks

This paper handles the simultaneous suppression of narrow-band and multiaccess interference in asynchronous CDMA networks. We consider both linear one-shot detection and block-detection, showing that, in both cases, the presence of an external narrow-band interferer generally results in the need for time-varying processing. As to the linear one-shot detectors, we derive both a zero-forcing and a minimum mean square error detector, showing that they are members of an only family, wherein the optimization criterion is the constrained minimization of a suitably defined output interference energy. We also present a comparative performance assessment between the various detection strategies, studying the impact of both the optimization criterion and other system parameters, such as the oversampling ratio and the length of the observation window. We also handle the problem of blind and adaptive detection. At first we show that the linear one-shot receivers are readily amenable to a blind implementation, upon off-line estimation of the covariance matrix of the observables. Next, we consider the problem of an adaptive implementation of a periodically time-varying minimum mean square error receiver, introducing and assessing a new cyclic recursive least squares (RLS) algorithm: we show that, unlike the conventional RLS algorithms, the new algorithm is capable of tracking the periodically time-varying variation of the receiver structure, induced by the presence of a data-like narrow-band interferer     

扩频系统中最优干扰抑制技术研究——盲自适应算法及并行实现

为解决扩频系统在动态环境下的干扰抑制问题,分析了从最小均方误差(MMSE)准则和约束最小均值输出能量(MMOE)准则导出的递推最小二乘(RLS)算法和盲递推最小二乘(BRLS)算法的性能。采用正交三角分解克服两算法数值稳定性差,运算量大,很难并行实现的缺点,讨论了正交三角分解——递推最小二乘(QR-RLS)算法与正交三角分解——盲递推最小二乘(QR-BRLS)算法的配合使用,并给出实现QR-RLS算法和QR-BRLS算法的脉动阵列(systolic array)。理论分析和仿真结果均表明QR-RLS与QR-BRLS算法的合理配合能较好的解决动态环境下的干扰抑制问题。     

Adaptive Reduced-Rank Processing Based on Joint and Iterative Interpolation, Decimation, and Filtering

We present an adaptive reduced-rank signal processing technique for performing dimensionality reduction in general adaptive filtering problems. The proposed method is based on the concept of joint and iterative interpolation, decimation and filtering. We describe an iterative least squares (LS) procedure to jointly optimize the interpolation, decimation and filtering tasks for reduced-rank adaptive filtering. In order to design the decimation unit, we present the optimal decimation scheme and also propose low-complexity decimation structures. We then develop low-complexity least-mean squares (LMS) and recursive least squares (RLS) algorithms for the proposed scheme along with automatic rank and branch adaptation techniques. An analysis of the convergence properties and issues of the proposed algorithms is carried out and the key features of the optimization problem such as the existence of multiple solutions are discussed. We consider the application of the proposed algorithms to interference suppression in code-division multiple-access (CDMA) systems. Simulations results show that the proposed algorithms outperform the best known reduced-rank schemes with lower complexity.     

Adaptive step-size algorithms for blind interference suppression inDS/CDMA systems

This paper develops adaptive step-size blind LMS algorithms and adaptive forgetting factor blind RLS algorithms for code-aided suppression of multiple access interference (MAI) and narrowband interference (NBI) in DS/CDMA systems. These algorithms optimally adapt both the step size (forgetting factor) and the weight vector of the blind linear multiuser detector using the received measurements. Simulations are provided to compare the proposed algorithms with previously studied blind RLS and blind LMS algorithms. They show that the adaptive step-size blind LMS algorithm and adaptive forgetting factor blind RLS algorithm field significant improvements over the standard blind LMS algorithm and blind RLS algorithm in dynamic environments where the number of interferers are time-varying     

Space-Time Adaptive MMSE Multiuser Decision Feedback Detectors With Multiple-Feedback Interference Cancellation for CDMA Systems

In this paper, we propose a novel space-time minimum mean square error (MMSE) decision feedback (DF) detection scheme for direct-sequence code-division multiple access (DS-CDMA) systems with multiple receive antennas, which employs multiple-parallel-feedback (MPF) branches for interference cancellation. The proposed space-time receiver is then further combined with cascaded DF stages to mitigate the deleterious effects of error propagation for uncoded schemes. To adjust the parameters of the receiver, we also present modified adaptive stochastic gradient (SG) and recursive least squares (RLS) algorithms that automatically switch to the best-available interference cancellation feedback branch and jointly estimate the feedforward and feedback filters. The performance of the system with beamforming and diversity configurations is also considered. Simulation results for an uplink scenario with uncoded systems show that the proposed space-time MPF-DF detector outperforms existing schemes such as linear, parallel DF (P-DF), and successive DF (S-DF) receivers in terms of bit error rate (BER) and achieves a substantial capacity increase in terms of the number of users, compared with the existing schemes. We also derive the expressions for MMSE achieved by the analyzed DF structures, including the novel scheme, with imperfect and perfect feedback and expressions of signal-to-interference-plus-noise ratio (SINR) for the beamforming and diversity configurations with linear receivers.     

Radio resource management for LTE-A relay-enhanced cells with spatial reuse and max–min fairness

One of the major issues in LTE-Advanced (LTE-A) systems is the poor capacity at the cell edge. This is mainly due to the interference experienced by the users as a result of the aggressive frequency reuse usually implemented. Relaying offers an attractive solution for this problem by offering better links than those with the eNodeB (eNB) for the terminals suffering from high path loss or high interference. However, adding relays complicates the resource allocation problem at the eNB and therefore the need for more efficient schemes arises. This is also aggravated by the reuse of resource blocks (RBs) by the relays to fully exploit the scarce spectrum, which, in turn, leads to intra-cell interference. In this paper, we study the joint power and resource allocation problem in LTE-A relay-enhanced cells that exploit spatial reuse. To guarantee fairness among users, a max–min fair optimization objective is used. This complex problem is solved using coordinate ascent and the difference of two convex functions (DC) programming techniques and the proposed scheme indeed converges to a local-optimum quickly. This is shown to be a satisfactory solution according to the simulation results that indicate an almost sevenfold increase in the 10th percentile capacity when compared to previously proposed solutions.     

Joint beamforming and power control in downlink multiuser multiple‐input multiple‐output systems

In this paper, we study joint beamforming and power control for downlink multiple‐input multiple‐output systems with multiple users and target values for signal‐to‐interference plus noise ratios (SINRs). We formulate this as a constrained optimization problem of minimizing total interference subject to constraints on the beamforming vector norms, target SINRs, and total transmit power. Necessary and sufficient conditions satisfied by the optimal beamformer and power allocation are presented, and a new algorithm for joint beamforming and power control is proposed. This adapts the beamforming vectors and transmit powers incrementally, and it stops when the specified SINR targets are achieved with minimum powers. The proposed algorithm is illustrated with numerical results obtained from simulations, which study its convergence and compare it with other similar algorithms. Copyright © 2013 John Wiley & Sons, Ltd.     

Adaptive space-time reduced-rank estimation based on diversity-combined decimation and interpolation applied to interference suppression in CDMA systems

An adaptive low-complexity space-time reduced-rank processor is proposed for interference suppression in asynchronous DS code division multiple access (CDMA) systems based on a diversity-combined decimation and interpolation method. The novel design approach for the processor employs an iterative procedure to jointly optimise the interpolation, decimation and estimation tasks for reduced-rank parameter estimation. Joint iterative least squares design parameter estimators are described and low-complexity adaptive recursive least squares (RLS) algorithms for the proposed structure are developed. To design the decimation unit, the optimal decimation scheme based on the counting principle is presented and lowcomplexity decimation structures are proposed. Linear space-time receivers with antenna arrays based on the proposed reduced-rank processor are then presented and investigated to mitigate multi-access interference and intersymbol interference in an asynchronous DS-CDMA system uplink scenario. An analysis of the convergence properties of the proposed space-time processor is carried out and analytical expressions are derived to predict the mean squared error performance of the proposed processor with RLS algorithms. Simulations show that the proposed processor outperforms the best known reduced-rank schemes at substantially lower complexity.     

Joint Beamforming and Power Allocation for Multiple Access Channels in Cognitive Radio Networks

A cognitive radio (CR) network refers to a secondary network operating in a frequency band originally licensed/allocated to a primary network consisting of one or multiple primary users (PUs). A fundamental challenge for realizing such a system is to ensure the quality of service (QoS) of the PUs as well as to maximize the throughput or ensure the QoS, such as signal-to-interference-plus-noise ratios (SINRs), of the secondary users (SUs). In this paper, we study single-input multiple output multiple access channels (SIMO-MAC) for the CR network. Subject to interference constraints for the PUs as well as peak power constraints for the SUs, two optimization problems involving a joint beamforming and power allocation for the CR network are considered: the sum-rate maximization problem and the SINR balancing problem. For the sum-rate maximization problem, zero-forcing based decision feedback equalizers are used to decouple the SIMO-MAC, and a capped multi-level (CML) water-filling algorithm is proposed to maximize the achievable sum-rate of the SUs for the single PU case. When multiple PUs exist, a recursive decoupled power allocation algorithm is proposed to derive the optimal power allocation solution. For the SINR balancing problem, it is shown that, using linear minimum mean-square-error receivers, each of the interference constraints and peak power constraints can be completely decoupled, and thus the multi-constraint optimization problem can be solved through multiple single-constraint sub-problems. Theoretical analysis for the proposed algorithms is presented, together with numerical simulations which compare the performances of different power allocation schemes.     

Optimal power allocation for cognitive radio networks with relay‐assisted directional transmission

In this paper, the problem of power allocation in a cooperative cognitive radio (CR) network is investigated. An optimal power allocation is proposed to maximize efficiency of the secondary network in which secondary users transmit simultaneously over a spectral band assigned to the primary users. The CR network employs directional relays to improve efficiency of the communication links and minimize interference introduced to the primary users. Unlike the conventional cooperative relay‐assisted network, the directional relays are grouped in clusters. This clustering technique along with directional transmission can significantly reduce interference to the primary links and improve the system performance. Two algorithms are also developed on the basis of the penalty method to determine unknown transmission powers. Some corroborant numerical examples are provided to illustrate quick convergence behavior of the proposed algorithms and great superiority of employing clustered directional relays in cooperative CR networks. Copyright © 2013 John Wiley & Sons, Ltd.     

A maximum likelihood approach to blind multiuser interferencecancellation

This paper addresses the problem of blind multiple access interference (MAI) and intersymbol interference (ISI) suppression in direct sequence code division multiple access (DS CDMA) systems. A novel approach to obtain the coefficients of a linear receiver using the maximum likelihood (ML) principle is proposed. The method is blind because it only exploits the statistical features of the transmitted symbols and Gaussian noise in the channel. We demonstrate that an adequate linear constraint on these coefficients ensures that the desired user is extracted and the resulting linearly constrained maximum likelihood linear (LCMLL) receiver can be efficiently implemented using the iterative space alternating generalized expectation-maximization (SAGE) algorithm. In order to take advantage of the diversity inherent to multipath channels, we also introduce a blind RAKE multiuser receiver that proceeds in two steps. First, soft estimates of the desired user transmitted symbols are obtained from each propagation path using a bank of appropriate LCMLL receivers. Afterwards, these estimates are adequately combined to enhance the signal-to-interference-and-noise ratio (SINR). Computer simulations show that the proposed blind algorithms for multiuser detection are near-far resistant and attain convergence using small blocks of data, thus outperforming existing linearly constrained minimum variance (LCMV) blind receivers     

Robust constrained linear receivers for CDMA wireless systems

For code-division multiple access (CDMA) communication systems, many constrained linear receivers have been developed to suppress multiple access interference. The linearly constrained formulations are generally sensitive to multipath fading and other types of signal mismatch. We develop robust linear receivers by exploring appropriate constraints. Multiple linear constraints are exploited to preserve the output energy that is scattered in multipath channels. In addition, a quadratic inequality constraint on the weight vector norm is used to improve robustness with respect to imprecise signal modeling. These constraints can be applied to the minimum output energy (MOE) detector to mitigate the signal mismatch problem and to the decision directed minimum mean square error (MMSE) detector to prevent error propagation and eliminate the need for training sequences at startup. Adaptive implementations for the proposed detectors are presented using recursive least square (RLS) updating in both the direct form and the partitioned linear interface canceller (PLIC) structure. Simulations are performed in a multipath propagation environment to illustrate the performance of the proposed detectors     

Dynamic resource allocation algorithm in multi-user cooperative OFDMA systems: considering QoS and fairness constraints

Wireless transmission systems are constrained by several parameters such as the available spectrum bandwidth, mobile battery energy, transmission channel impairments and users’ minimum quality-of-service. In this paper, a new strategy is investigated that aims at improving the allocation of resources in a dual hop OFDMA cooperative network consisting in multi source–destination pairs and multiple decode-and-forward relays. First, the joint optimization of three types of resources: power, sub-channel and relay nodes, is formulated as a problem of subchannel-relay assignment and power allocation, with the objective of minimizing overall transmission power under the bit-error-rate and data rate constraints. However, the optimal solution to the optimization problem is computationally complex to obtain and may be unfair. Assuming knowledge of the instantaneous channel gains for all links in the entire network, an iterative three-step resource allocation algorithm with low complexity is proposed. In order to guarantee the fairness of users, several fairness criteria are also proposed to provide attractive trade-offs between network performance (i.e. overall transmission power, average network lifetime and average outage probability) and fairness to all users. Numerical studies are conducted to evaluate the performance of the proposed algorithm in two practical scenarios. Simulation results show that the proposed allocation algorithm achieves an efficient trade-off between network performance and fairness among users.     

Adaptive resource allocation for multiaccess MIMO/OFDM systems with matched filtering

In this letter, we propose an adaptive resource-allocation algorithm for multiaccess multiple-input multiple-output/orthogonal frequency-division multiplexing systems. The proposed algorithm endeavors to maximize the system power efficiency, given that the users' quality of service (QoS) requirements, specified by bit-error rate and data rate, are satisfied. Subcarrier allocation, power distribution, and modulation for multiple users are jointly optimized according to users' channel states and QoS requirements. To avoid the joint optimization of resource allocation and beamforming, matched-filter-based receivers are employed at the base station, with cochannel interference being mitigated through dynamic subchannel allocation. A neighborhood search scheme is further developed to obtain a good allocation solution with reasonable computational efforts. Our results show that the proposed algorithm is able to achieve significant enhancement in the system power efficiency due to the successful exploitation of multiuser diversity, as well as channel variations in the time, frequency, and space domains.     

Cooperative Subcarrier Allocation and Power Allocation in the Downlink of an Amplify-and-Forward OFDM Relaying System

The increasing use of relays in wireless communication systems is a driving force to explore innovative techniques that can improve the quality of service as well as enhance the coverage in wireless systems. In this article, we propose a two-step approach for subcarrier allocation and power allocation in the downlink of an OFDM-based amplify-and forward relaying system. In the first step, the total power is allocated to mobile users and relays based on the optimum power ratio derived for the single-relay system. In the second step, subcarriers are assigned to the users based on cooperative subcarrier allocation algorithms. Compared to the non-cooperative algorithm with flat power allocation, the total throughput is shown to improve by applying the two-step cooperative subcarrier allocation and power allocation algorithms.     

Blind Adaptive and Iterative Algorithms for Decision-Feedback DS-CDMA Receivers in Frequency-Selective Channels

In this paper, we examine blind adaptive and iterative decision-feedback (DF) receivers for direct-sequence code-division multiple-access systems in frequency-selective channels. Code-constrained minimum variance and constant modulus design criteria for DF receivers based on constrained optimization techniques are investigated for scenarios subject to multipath. Computationally efficient blind adaptive stochastic gradient and recursive least squares algorithms are developed for estimating the parameters of DF detectors along with successive, parallel, and iterative DF structures. A novel successive parallel arbitrated DF scheme is presented and combined with iterative techniques for use with cascaded DF stages in order to mitigate the deleterious effects of error propagation. Simulation results for an uplink scenario assess the algorithms and the blind adaptive DF detectors against linear receivers and evaluate the effects of error propagation of the new cancellation techniques against previously reported approaches     

Energy‐efficient outage‐constrained power allocation based on statistical channel knowledge for dual‐hop cognitive relay networks

This paper investigates the power allocation problem in decode‐and‐forward cognitive dual‐hop systems over Rayleigh fading channels. In order to optimize the performance of the secondary network in terms of power consumption, an outage‐constrained power allocation scheme is proposed. The secondary nodes adjust their transmit power subject to an average interference constraint at the primary receiver and an outage probability constraint for the secondary receivers while having only statistical channel knowledge with respect to the primary nodes. We compare this approach with a power allocation scheme based on instantaneous channel state information under a peak interference constraint. Analytical and numerical results show that the proposed approach, without requiring the constant interchange of channel state information, can achieve a similar performance in terms of outage probability as that of power allocation based on instantaneous channel knowledge. Moreover, the transmit power allocated by the proposed approach is considerably smaller than the power allocated by the method based on instantaneous channel knowledge in more than 50% of the time. Copyright © 2015 John Wiley & Sons, Ltd.