On the macroscopic optimization of multicell wireless systems with multiuser detection and multiple antennas - uplink analysis

In this paper, we consider a system with K single-antenna client users, n/sub B/ base stations (each base station has n/sub R/ antennas), as well as a centralized controller. A client user could be associated with a single base station at any time. All the base stations operate at the same frequency and have optimal multiuser detection per base station which cancels intracell interference only. We consider a general problem of uplink macroscopic resource management where the centralized controller dynamically determines an appropriate association mapping of the K users with respect to the n/sub B/ base stations over a macroscopic time scale. We propose a novel analytical framework for the above macroscopic scheduling problems. A simple rule is to associate a user with the strongest base station (camp-on-the-strongest-cell), and this has been widely employed in conventional cellular systems. However, based on the optimization framework, we found that this conventional approach is in fact not optimal when multiuser detection is employed at the base station. We show that the optimal macroscopic scheduling algorithm is of exponential complexity, and we propose a simple greedy algorithm as a feasible solution.     

Efficient user selection for multi-cell multi-user MIMO systems with limited backhaul

Multi-cell multi-user multiple-input multiple-output (MC-MU-MIMO) is a promising technique to eliminate inter-user interference and inter-cell cochannel interference in wireless telecommunication syste...     

Multistage weighted interference cancellation with receiver diversity for DS-CDMA

Conventional multistage multiuser detectors (MUDs) such as parallel interference cancellation (PIC) suffer from error propagation. In this paper, we propose a generalized multistage MUD with receiver diversity, which is referred to as weighted interference cancellation (WIC), in which reliability weighting factors and user-decision ordering are applied to reduce error propagation. Two flavors (the parallelizable and nonparallelizabe WIC) are presented in this paper. An algorithm is next derived for the joint determination of the reliability weighting factors and weightings for linear diversity combining. Two selection diversity schemes are also presented as lower complexity alternatives to linear diversity combining. Finally, sorting algorithms for determining the user decision order are also proposed. Simulation results show that the proposed MUD achieves very good performance. For E/sub b//N/sub 0/<20 dB, using just a few stages, certain variations of the proposed MUD almost achieve the single user bound with one antenna when the number of active users is smaller than 15 and with two antennas when the number of users is smaller than 30.     

Power control and clustering in heterogeneous cellular networks

Recently, it is widely believed that significant coverage and performance improvement can be achieved through the deployment of small cells in conjunction with the well-established macro cells. However, it is expected that the high density of base stations in such heterogeneous cellular networks will give rise to multiple design problems related to both co-tier (small-to-small) and cross-tier (between small and macro cells) interference. Fortunately, cooperation between base stations will play a major role to cope with these problems and hence to enhance the users’ data rates. In this paper, we consider a two-tier cellular network comprised of a macro cell underlaid with multiple small cells where both co-tier and cross-tier interference are taken into account. We study the scenario where the small cell base stations seek to maximize a common objective by forming multiple clusters through cooperation. These base stations have also to allocate power to their associated users and, at the same time, control the total aggregate interference caused to the macro cell user which has to be kept below a threshold prefixed by the macro cell base station. We consider two utility functions: the overall sum rate of the small cell network and the minimum data rate of the small cell users. We formulate the studied problems as mixed integer nonlinear optimization problems and we discuss their NP hardness. Therefore, due to the complexity of finding the optimal solution, we design heuristic algorithms which resolves efficiently the tradeoff between computational complexity and performance. We show through simulations that the designed heuristics approach the optimal solution (obtained using the complex exhaustive search algorithm) with highly reduced computational complexity.     

Robust uplink power control for co-channel two-tier femtocell networks

This paper is concerned with uplink interference suppression problem in two-tier femtocell networks through power control. Specifically, we consider the Quality-of-Service (QoS) of the macrocell user and femtocell users in terms of their received Signal to Interference-plus-Noise Ratios (SINRs) at macrocell base station (MBS) and femtocell base stations (FBSs), and we also take femtocell users’ power efficiency into consideration by designing an objective function, which is a weighted sum of transmission power and squared SINR difference between femtocell user's maximum SINR and actual SINR. Due to the error of the SINR at MBS caused by distance errors, a robust uplink power control problem is formulated, and it is equivalent to a robust convex optimization problem with femtocell users’ SINR constraints. Then, the robust convex optimization problem is converted into a general convex optimization problem. Moreover, a distributed power control algorithm combined with admission control is presented to obtain femtocell users’ optimal power allocation. Numerical results show the convergence and effectiveness of the proposed uplink power control algorithm.     

一种多人多出DS/CDMA系统中的半盲多用户检测算法

多用户检测技术是DS/CDMA中的一项关键技术,而天线阵的广泛应用也促使对多入多出系统的研究。该文将两种技术结合在一起,考虑到基站在一般情况下总是知道本小区的多个用户的扩频码,在此半盲意义下研究了将子空间方法应用于多用户检测的技术。这种技术可适用于低速移动台在慢衰落信道下的盲检测。仿真结果表明这种算法相对于只利用一个用户的扩频码的盲检测算法性能有相当大的提高。     

Proportional Fair Space–Time Scheduling for Wireless Communications

We extend the proportional fair (PF) scheduling algorithm to systems with multiple antennas. There are$K$client users (each with a single antenna) and one base station (with$n_R$antennas). We focus on the reverse link of the system, and assume a slow-fading channel where clients are moving with pedestrian speed. Qualcomm's original PF scheduling algorithm satisfies the PF criteria only when the communication is constrained to one user at a time with no power waterfilling. However, the original PF algorithm does not generalize easily when we have$n_R$receive antennas at the base station. In this paper, we shall formulate the PF scheduling design as a convex optimization problem. One challenge is in the optimal power allocation over the multiantenna multiaccess capacity region, which is still an open problem. For practical consideration, we consider multiuser minimum mean-square error processing at the base station. To obtain first-order insight, we propose an asymptotically optimal PF scheduling solution. Using the proposed PF solution for a multiantenna base station, the system capacity is enhanced by exploiting the multiuser selection diversity, as well as the distributed multiple-input multiple-output configuration. It is found that the PF scheduler achieves a good balance between fairness and system capacity gain.     

On multicell cooperative transmission in backhaul-constrained cellular systems

Recent work has shown that multicell cooperative signal processing in cellular networks can significantly increase system capacity and fairness. For example, multicell joint transmission and joint detection can be performed to combat intercell interference, often mentioned in the context of distributed antenna systems. Most publications in this field assume that an infinite amount of information can be exchanged between the cooperating base stations, neglecting the main downside of such systems, namely, the need for an additional network backhaul. In recent publications, we have thus proposed an optimization framework and algorithm that applies multicell signal processing to only a carefully selected subset of users for cellular systems with a strongly constrained backhaul. In this paper, we consider the cellular downlink and provide a comprehensive summary and extension of our previous and current work. We compare the performance obtained through centralized or decentralized optimization approaches, or through optimal or suboptimal calculation of precoding matrices, and identify reasonable performance–complexity trade-offs. It is shown that even low-complexity optimization approaches for cellular systems with a strongly constrained backhaul can yield major performance improvements over conventional systems.     

A distributed implementation of mobility load balancing with power control and cell reselection in 4G network

We consider a self‐organizing network (SON) capability of mobility load balancing in a 4G network, which determines the transmission power level for individual base stations and cell reselection for individual mobile stations such that the network‐wide load is minimized while satisfying the minimum signal‐to‐noise and interference ratio (SINR) requirement of individual users. Both centralized and distributed schemes are proposed. The centralized scheme is based on the greedy algorithm, serving as a performance bound to the distributed scheme. The distributed scheme is to solve the system‐wide optimization problem in the flat network model, i.e. no central control node. Furthermore, it requires relatively low inter‐cell exchange information among neighboring cells over an inter‐cell channel, e.g. X2 interface in the LTE network. The proposed design objective is to minimize the number of mobile users that do not satisfy the specified average throughput, while distributing the user traffic load as uniformly as possible among the neighboring cells. Our simulation results for a uniform user distribution demonstrate that the proposed scheme can achieve up to almost 80% of a load balancing gain that has been achieved by a greedy algorithm in the centralized optimization. Copyright © 2014 John Wiley & Sons, Ltd.     

基于深度学习的毫米波系统波束成形

针对高移动用户在毫米波系统中用户与基站之间频繁切换增大延迟开销问题,提出了一种新颖的集成深度学习协调波束成形(Deep Learning Coordinated Beamforming,DLCBF)解决方案.该方案通过协调多个基站同时为一个移动用户服务,接收用户上行导频序列和预编码码本训练模型,进而预测最佳下行波束向量...     

Performance analysis of SIMO space-time scheduling with convex utility function: zero-forcing linear processing

In a multiple-antenna system, an optimized design across the link and scheduling layers is crucial toward fully exploiting the temporal and spatial dimensions of the communication channel. In this paper, based on discrete optimization techniques, we derive a novel analytical framework for designing optimal space-time scheduling algorithms with respect to general convex utility functions. We focus on the reverse link (i.e., client to base station) and assume that the mobile terminal has a single transmit antenna while the base station has n/sub R/ receive antennas. In order that our proposed framework is practicable and can be implemented with a reasonable cost in a real environment, we further assume that the physical layer involves only linear-processing complexity in separating signals from different users. As an illustration of the efficacy of our proposed analytical design framework, we apply the framework to two commonly used system utility functions, namely maximal throughput and proportional fair. We then devise an optimal scheduling algorithm based on our design framework. However, in view of the formidable time complexity of the optimal algorithm, we propose two fast practical scheduling techniques, namely the greedy algorithm and the genetic algorithm (GA). The greedy algorithm, which is similar to the one widely used in 3G1X and Qualcomm high-data-rate (HDR) systems (optimal when n/sub R/=1), exhibits significantly inferior performance when n/sub R/>1 as compared with the optimal approach. On the other hand, the GA is quite promising in terms of performance complexity tradeoff, especially for a system with a large number of users with even a moderately large n/sub R/. As a case in point, for a system with 20 users and n/sub R/=4, the GA is more than 36 times faster than the optimal while the performance degradation is less than 10%, making it an attractive choice in the practical implementation for real-time link scheduling.     

A game-theoretic approach to decentralized optimal power allocation for cellular networks

The rapidly growing demand for wireless communication makes efficient power allocation a critical factor in the network??s efficient operation. Power allocation in cellular networks with interference, where users are selfish, has been recently studied by pricing methods. However, pricing methods do not result in efficient/optimal power allocations for such systems for the following reason. Because of interference, the communication between the Base Station (BS) and a given user is affected by that between the BS and all other users. Thus, the power vector consisting of the transmission power in each BS-user link can be viewed as a public good which simultaneously affects the utilities of all the users in the network. It is well known (Mas-Colell et al., Microeconomic Theory, Oxford University Press, London, 2002, Chap. 11.C) that in public good economies, standard efficiency theorems on market equilibrium do not apply and pricing mechanisms do not result in globally optimal allocations. In this paper we study power allocation in the presence of interference for a single cell wireless Code Division Multiple Access (CDMA) network from a game theoretic perspective. We consider a network where each user knows only its own utility and the channel gain from the base station to itself. We formulate the uplink power allocation problem as a public good allocation problem. We present a game form the Nash Equilibria of which yield power allocations that are optimal solutions of the corresponding centralized uplink network.     

Scheduling Algorithms and Throughput Maximization for the Downlink of Packet-Data Cellular Systems with Multiple Antennas at the Base Station

The capacity-achieving coding scheme for the multiple-input multiple-output (MIMO) broadcast channel is dirty-paper coding. With this type of transmission scheme the optimal number of active users that receive data and the optimal power allocation strategy are highly dependent on the structure of the channel matrix and on the total transmit power available. In the context of packet-data access with adaptive transmission where mobile users are equipped with a single receive antenna and the base station has multiple transmit antennas, we study the optimal number of active users and the optimal power allocation. In the particular case of two transmit antennas, we prove that the optimal number of active users can be a non-monotonic function of the total transmit power. Thus not only the number of users that should optimally be served simultaneously depends on the user channel vectors but also on the power available at the base station transmitter. The expected complexity of optimal scheduling algorithms is thus very high. Yet we then prove that at most as many users as the number of transmit antennas are allocated a large amount of power asymptotically in the high-power region in order to achieve the sum-capacity. Simulations confirm that constraining the number of active users to be no more than the number of transmit antennas incurs only a marginal loss in spectral efficiency. Based on these observations, we propose low-complexity scheduling algorithms with sub-optimal transmission schemes that can approach the sum-capacity of the MIMO broadcast channel by taking advantage of multiuser diversity. The suitability of known antenna selection algorithms is also demonstrated. We consider the cases of complete and partial channel knowledge at the transmitter. We provide simulation results to illustrate our conclusions.     

Space-time turbo multiuser detection for coded MC-CDMA

The system capacity and performance of multicarrier code-division multiple-access (MC-CDMA) communication systems can be significantly enhanced by jointly employing MAP-based multiuser detection (MUD) and channel decoding techniques. In this paper, a group-oriented soft iterative MUD based on the combination of smart antennas and iterative MAP-based MUD is presented. The proposed method is featured as a novel technique for further increasing the system capacity and performance. In this method, all the users are first grouped into several groups according to their impinging direction of arrivals (DOAs). All users with similar DOAs are classified into the same group and then low-complexity MAP-based iterative MUD is employed in each group. Because spatial filtering cannot suppress all the interference between the groups, interference cancellation among the groups is used prior to MUD within each group. It is shown that the proposed group-oriented soft iterative MUD algorithm can significantly reduce the computational complexity compared with the conventional optimal MAP-based MUD schemes. It is also demonstrated that the performance of the proposed algorithm can approach that of a single-user coded MC-CDMA system with an antenna array in additive white Gaussian noise and frequency selective fading channels.     

Joint admission control,cell association,power allocation and throughput maximization in decoupled 5G heterogeneous networks

Downlink (DL)-uplink (UL) coupled cell association scheme was adopted in 3rd generation (3G) homogeneous network and 4th generation (4G) heterogeneous network (HetNet). In the coupled cell association scheme, a user is associated to single base station (BS) in DL & UL based on the strongest received signal power (SRSP) in DL from a macro base station (MBS) and multiple small base stations (SBS) in HetNet. This is a sub-optimal solution for cell association as most of the users are associated to a MBS due to dominant transmit power and brings challenges like multiple interference issues and imbalanced user traffic load which leads to a degraded throughput in HetNet. In this paper, we investigate downlink uplink decoupled cell association scheme to address these issues and formulate a sum-rate maximization problem in terms of admission control, cell association and power allocation for MBS only, coupled and decoupled HetNet. The formulated optimization problem falls into class of a mixed integer non linear programming (MINLP) problem which is NP-hard and requires exhaustive search to find the optimal solution. However, computational complexity of the exhaustive search increases exponentially with the increase in number of users. Therefore, an outer approximation algorithm (OAA) is proposed as a solution to find near optimal solution with less computation complexity. Extensive simulations work has been done to evaluate the decoupled cell association scheme in HetNet vs the coupled cell association scheme in traditional MBS only and HetNet. Results show the effectiveness of decoupled cell association scheme in terms of KPIs, such as throughput, addressing user traffic load imbalances and number of users attached.

     

Adaptive antennas at the mobile and base stations in an OFDM/TDMAsystem

Several smart antenna systems have been proposed and demonstrated at the base station (BS) of wireless communications systems, and these have shown that significant system performance improvement is possible. We consider the use of adaptive antennas at the BS and mobile stations (MS), operating jointly, in combination with orthogonal frequency-division multiplexing. The advantages of the proposed system includes reductions in average error probability and increases in capacity compared to conventional systems. Multiuser access, in space, time, and through subcarriers, is also possible and expressions for the exact joint optimal antenna weights at the BS and MS under cochannel interference conditions for fading channels are derived. To demonstrate the potential of our proposed system, analytical along with Monte Carlo simulation results are provided     

基于人工蜂群算法的基站天线方位角与下倾角自优化方法

针对3GPP中提出的SON(self-organizing network,自组织网络)覆盖自优化问题,提出一种基于人工蜂群算法的基站天线方位角与下倾角同时优化方法。首先,基站根据用户设备上报的MR(measurement report,测量报告)数据确定待优化区域,并建立以基站天线对待优化区域的平均增益为目标函数的优化模型;其次,利用人工蜂群算法求解该目标函数,并得到基站天线方位角与下倾角的最优解;最后,将基站天线方位角与下倾角调整至最佳值,实现基站根据用户设备位置的覆盖自优化。通过系统建模、仿真与外场实验,以用户设备接收的RSRP(reference signal receiving power,参考信号接收功率)为指标,利用人工蜂群算法的计算方法较未优化的初始参数提升6.81 dB,较依靠人工经验的判别方法提升4.35 dB。实验结果证明,提出的自优化方法可根据用户位置分布精准及时地对基站天线方位角与下倾角进行调整,提升用户对信号强度的感知。     

A framework for uplink power control in cellular radio systems

In cellular wireless communication systems, transmitted power is regulated to provide each user an acceptable connection by limiting the interference caused by other users. Several models have been considered including: (1) fixed base station assignment where the assignment of users to base stations is fixed, (2) minimum power assignment where a user is iteratively assigned to the base station at which its signal to interference ratio is highest, and (3) diversity reception where a user's signal is combined from several or perhaps all base stations. For the above models, the uplink power control problem can be reduced to finding a vector p of users' transmitter powers satisfying p⩾I(p) where the jth constraint p_j⩾I_j(p) describes the interference that user j must overcome to achieve an acceptable connection. This work unifies results found for these systems by identifying common properties of the interference constraints. It is also shown that systems in which transmitter powers are subject to maximum power limitations share these common properties. These properties permit a general proof of the synchronous and totally asynchronous convergence of the iteration p(t+1)=I(p(t)) to a unique fixed point at which total transmitted power is minimized     

On the capacity of the vector MAC with feedback

In this correspondence, we determine the feedback capacity region of a two user Gaussian multiple-access channel (MAC) with multiple antennas at the base station and a single antenna at each user. The vector MAC with a single antenna at the base station and multiple antennas at each user is shown to be equivalent to a scalar MAC. We also determine the capacity enhancement due to feedback at high signal-to-noise ratio (SNR) for the scalar and vector MAC for any number of users. Extensions of the high SNR results to the vector broadcast channel are also provided.     

分布式MIMO系统发送天线选择与预编码联合设计

为了抑制多用户分布式多入多出(MIMO)系统中的同道干扰(CCI),使系统同时服务于更多用户,提出一种发送天线选择与预编码的联合设计方法。该方法立足于分布式MIMO系统基站端天线较多的特点,将下行发送天线选择与信漏噪比(SLNR)预编码相结合,通过为用户选择不同天线,从根本上减少CCI;在为每个用户选择天线时,先以信道子矩阵的迹为依据进行端口选择,再采用逐减的方法选择使SLNR损失值最小的天线,以保证每个用户对其他用户的干扰尽量小,从而达到进一步抑制CCI的目的。复杂度分析和仿真结果表明,该方法在具有较低复杂度同时,其容量性能仍可逼近最优算法;较之单纯的SLNR预编码,在相同的容量性能约束下,其能够有效增加系统同时服务的用户数。