Multi-cell MIMO Research Articles

Exploiting Base Station Caching in MIMO Cellular Networks: Opportunistic Cooperation for Video Streaming

We propose a novel MIMO cooperation framework called the cache-induced opportunistic cooperative MIMO (Coop-MIMO) for video streaming in backhaul limited multicell MIMO networks. By caching a portion of the video files, the base stations (BSs) opportunistically employ Coop-MIMO transmission to achieve MIMO cooperation gain without expensive payload backhaul. We derive closed form expressions of various video streaming performance metrics for cache-induced opportunistic Coop-MIMO and investigate the impact of BS level caching and key system parameters on the performance. Specifically, we first obtain a mixed fluid-diffusion limit for the playback buffer queueing system. Then we derive the approximated video streaming performance using the mixed fluid-diffusion limit. Based on the performance analysis, we formulate the joint optimization of cache control and playback buffer management as a stochastic optimization problem. Then we derive a closed form solution for the playback buffer thresholds and develop a stochastic subgradient algorithm to find the optimal cache control. The analysis shows that the video streaming performance improves linearly with the BS cache size BC, the transmit power cost decreases exponentially with BC, and the backhaul cost decreases linearly with BC.

多基站多用户MIMO系统下行链路基于准最大化和速率预编码和功率分配的双层交替迭代结构

In multi-cell multiuser MIMO systems, the precoder of maximizing sum-rate (MSR) is optimal in linear and sum rate senses. However, there is no closed-form solution for MSR. In this paper, an alternating iterative quasi-MSR precoder of approaching MSR is developed by transforming the MSR problem into the one maximizing the product of fractional quadratic functions. In addition, a low-complexity alternating grid search power allocation (AGSPA) method is designed based on MSR principle in the case of single receive antenna per user. Then, an alternating iterative structure (AIS) between the proposed quasi-MSR and the low-complexity AGSPA is proposed. From simulations, the proposed AIS performs much better than the four common precoders maximizing signal-to-leakage-and-noise ratio, block diagonalization, minimum mean square error, and rate maximization in terms of sum rate in the presence of large-scale fading and antenna correlation.

Linear Precoding Based on Polynomial Expansion: Large-Scale Multi-Cell MIMO Systems

Large-scale MIMO systems can yield a substantial improvement in spectral efficiency for future communication systems. Due to the finer spatial resolution achieved by a huge number of antennas at the base stations, these systems have shown to be robust to inter-user interference and the use of linear precoding is asymptotically optimal. However, most precoding schemes exhibit high computational complexity as the system dimensions increase. For example, the near-optimal RZF requires the inversion of a large matrix. This motivated our companion paper, where we proposed to solve the issue in single-cell multi-user systems by approximating the matrix inverse by a truncated polynomial expansion (TPE), where the polynomial coefficients are optimized to maximize the system performance. We have shown that the proposed TPE precoding with a small number of coefficients reaches almost the performance of RZF but never exceeds it. In a realistic multi-cell scenario involving large-scale multi-user MIMO systems, the optimization of RZF precoding has thus far not been feasible. This is mainly attributed to the high complexity of the scenario and the non-linear impact of the necessary regularizing parameters. On the other hand, the scalar weights in TPE precoding give hope for possible throughput optimization. Following the same methodology as in the companion paper, we exploit random matrix theory to derive a deterministic expression for the asymptotic SINR for each user. We also provide an optimization algorithm to approximate the weights that maximize the network-wide weighted max-min fairness. The optimization weights can be used to mimic the user throughput distribution of RZF precoding. Using simulations, we compare the network throughput of the TPE precoding with that of the suboptimal RZF scheme and show that our scheme can achieve higher throughput using a TPE order of only 3.

Vidyut

Global synchronization across time and frequency domains significantly benefits wireless communications. Multi-Cell (Network) MIMO, interference alignment solutions, opportunistic routing techniques in ad-hoc networks, OFDMA etc. all necessitate synchronization in either time or frequency domain or both. This paper presents sysname, a system that exploits the easily accessible and ubiquitous power line infrastructure to achieve synchronization in time and frequency domains across nodes distributed beyond a single-collision domain. sysname uses the power lines to transmit a reference frequency tone to which each node locks its frequency. sysname exploits the steady periodicity of delivered power signal itself to synchronize distributed nodes in time. We validate the extent of sysname's synchronization and evaluate its effectiveness. We verify sysname's suitability for wireless applications such as OFDMA and multi-cell MIMO by validating the benefits of global synchronization in an enterprise wireless network. Our experiments show a throughput gain of 8.2x over MegaMIMO, 7x over NemoX and 2.5x over OFDMA systems. Enterprise wireless networks are supported by an Ethernet backbone. Researchers have been exploring techniques over the backbone to enable and assist in improving the performance of the wireless networks. Recent work also showed the benefit of sharing information in the air between the nodes to enable higher performance of the network. Even sharing information as little as synchronization information has been demonstrated to open new avenues (such as MU-MIMO, Physical Network Coding, Opportunistic routing, etc.) for the wireless networks to enhance its performance. However, another medium shared by majority of the nodes in the enterprise network - the power line infrastructure - has been largely left untapped to assist the wireless network. While the power lines are noisy and have a frequency selective transmission characteristic, its uniqueness is that its range can extend beyond that over air while it is unburdened by switching and other responsibilities of the Ethernet backbone. This paper poses the following question: How best to exploit the opportunity presented by the power lines to further enhance enterprise wireless networks? The key contributions of this paper are the following: Identify and demonstrate the feasibility of utilizing power lines as a medium to achieve synchronization (in time and frequency domains) between nodes in the network; Demonstrate the scalability of this technique by achieving synchronization between nodes beyond the transmission range of any of the individual nodes. The paper presents empirical results pertaining to the accuracy of synchronization and the benefit of the proposed synchronization method to existing distributed wireless techniques by virtue of extension across multiple collision domains.

Uplink Linear Receivers for Multi-Cell Multiuser MIMO With Pilot Contamination: Large System Analysis

Base stations with a large number of transmit antennas can potentially serve a large number of users at high rates. However, the receiver processing in the uplink relies on channel estimates, which are known to suffer from pilot interference. In this paper, making use of the similarity of the uplink received signal in CDMA with that of a multi-cell multi-antenna system, we perform a large system analysis when the receiver employs an MMSE filter with a pilot contaminated estimate. We assume a Rayleigh fading channel with different received powers from users. We find the asymptotic signal to interference plus noise ratio (SINR) as the number of antennas and number of users per base station grow larger while maintaining a fixed ratio. Through the SINR expression we explore the scenario where the number of users being served are comparable to the number of antennas at the base station. The SINR explicitly captures the effect of pilot contamination and is found to be the same as that employing a matched filter with a pilot contaminated estimate. We also find the exact expression for the interference suppression obtained using an MMSE filter, which is an important factor when there are a significant number of users in the system as compared to the number of antennas. In a typical set up, in terms of the five percentile SINR, the MMSE filter is shown to provide significant gains over matched filtering and is within 5 dB of MMSE filter with perfect channel estimate. Simulation results for achievable rates are close to large system limits for even a 10-antenna base station with 3 or more users per cell.

Robust Transceiver Design for Multicell MIMO Downlink Systems

The robust linear transceiver design for the more general model of multicell MIMO downlink system with imperfect channel state information is discussed in this paper. Our aim is to minimize the total power of the network while the quality of service (QoS) in terms of mean-square error (MSE) for every user should be strictly guaranteed for every channel realization in the uncertain region. Unfortunately, this problem may be infeasible due to the MSE constraints. Therefore, we provide a complete analysis of this problem by dividing the solutions into two phases. In phase I, a novel approach is devised to check the feasibility of this problem by considering one alternative problem which is always feasible. This alternative problem is troublesome due to infinite nonconvex MSE constraints. To handle this, we propose an iterative algorithm that performs optimization alternatively by switching between the precoders and decoders. The two subproblems in the algorithm can be recast as semidefinite programming problems which can be efficiently solved. In phase II, one novel iterative algorithm is proposed to solve the original robust problem. Finally, simulation results show that our proposed algorithms converge rapidly and can provide guaranteed QoS for all users. Moreover, we also show that, the more antennas at the users, the more power savings it can provide.

Uplink Sum-Rate Analysis of Massive MIMO System with Pilot Contamination and CSI Delay

We consider multi-cell multi-user massive MIMO system under correlated Rayleigh fading channels. Taking pilot contamination and CSI delay into consideration, we derive the equivalent channel model with MMSE channel estimation and one-tap prediction. Employing this equivalent channel model, the lower bound of the uplink sum-rate is derived, and its asymptotical performance is studied when the base station antenna number goes without bound. We find that if we schedule the $$k$$ k -th user of all cells who have the same prediction coefficient, the uplink sum-rate is the same as the one with no CSI delay when the number of BS antennas goes without bound at a much greater rate than the number of users. Simulation results show that the asymptotic approximation has good performance for large $$M$$ M , and suggest that large antenna array can compensate for the decay due to CSI delay. Simulation results also verify our guess that CSI delay does not necessarilly decrease the uplink sum-rate due to the impact of pilot contamination.

Sum-Rate Maximization in the Multicell MIMO Multiple-Access Channel with Interference Coordination

This paper is concerned with the maximization of the weighted sum-rate (WSR) in the multicell MIMO multiple access channel (MAC). We consider a multicell network operating on the same frequency channel with multiple mobile stations (MS) per cell. Assuming the interference coordination mode in the multicell network, each base-station (BS) only decodes the signals for the MSs within its cell, while the inter-cell transmissions are treated as noise. Nonetheless, the uplink precoders are jointly optimized at MSs through the coordination among the cells in order to maximize the network weighted sum-rate (WSR). Since this WSR maximization problem is shown to be nonconvex, obtaining its globally optimal solution is rather computationally complex. Thus, our focus in this work is on low-complexity algorithms to obtain at least locally optimal solutions. Specifically, we propose two iterative algorithms: one is based on successive convex approximation and the other is based on iterative minimization of weighted mean squared error. Both solution approaches shall then reveal the structure of the optimal uplink precoders. In addition, we also show that the proposed algorithms can be implemented in a distributed manner across the coordinated cells. Simulation results show a significant improvement in the network sum-rate by the proposed algorithms, compared to the case with no interference coordination.

Limited Feedback for Cooperative Multicell MIMO Systems with Multiple Receive Antennas

Limited Feedback for Cooperative Multicell MIMO Systems with Multiple Receive Antennas

A low-complexity user selection scheme in a multicell MIMO environment

Abstract An efficient user selection scheme for the downlink of multiuser MIMO systems is proposed in a multicell environment. In a multicell environment, the intercell interference is one of the most influential factors limiting the performance. Thus, a user selection scheme that considers intercell interference is essential to increase the sum rate. The proposed scheme is based on an interference-aware precoding. It sequentially selects users such that the sum rate is maximized. In particular, we develop a simple incremental metric for the sum rate. The use of the derived metric enables a significant reduction in the computational complexity of the user selection process, as compared to the optimal exhaustive search. Numerical results show that the proposed scheme provides near-optimal performance with substantially reduced complexity.

Effective CSI Signaling and Decentralized Beam Coordination in TDD Multi-Cell MIMO Systems

We propose decentralized algorithms and corresponding signaling concepts of effective channel state information (CSI) for weighted sum rate (WSR) maximization via linear downlink transmit-receive beamforming in multi-cell multi-user MIMO systems operating in the time-division duplex (TDD) mode. The iterative processing consists of optimization steps that are run locally by base stations (BS), and facilitated by a combination of over-the-air uplink pilot signaling and scalar backhaul information exchange. In the first novel strategy, the coordinating cells update their transmit precoders and receivers by executing a cell-specific optimization loop one cell at a time, which guarantees monotonic convergence of the network-wide problem. The strategy employs separate uplink channel sounding (CS) and busy burst (BB) signaling to reveal the effective channels of the terminals to the neighboring BSs. In the second strategy, we sacrifice the monotonic convergence and devise a faster scheme where the BSs are allowed to optimize their variables in parallel based on just the CS responses and additional backhaul information. We make use of the optimization framework where the WSR maximization is carried out via weighted sum mean-squared-error (MSE) minimization, and generalize the approach by employing antenna-specific transmit power constraints. The numerical results demonstrate that WSR maximization has the desirable property that spatial scheduling, or user and beam selection, is carried out implicitly.

Joint Base Station Clustering and Beamformer Design for Partial Coordinated Transmission in Heterogeneous Networks

We consider the interference management problem in a multicell MIMO heterogeneous network. Within each cell there is a large number of distributed micro/pico base stations (BSs) that can be potentially coordinated for joint transmission. To reduce coordination overhead, we consider user-centric BS clustering so that each user is served by only a small number of (potentially overlapping) BSs. Thus, given the channel state information, our objective is to jointly design the BS clustering and the linear beamformers for all BSs in the network. In this paper, we formulate this problem from a {sparse optimization} perspective, and propose an efficient algorithm that is based on iteratively solving a sequence of group LASSO problems. A novel feature of the proposed algorithm is that it performs BS clustering and beamformer design jointly rather than separately as is done in the existing approaches for partial coordinated transmission. Moreover, the cluster size can be controlled by adjusting a single penalty parameter in the nonsmooth regularized utility function. The convergence of the proposed algorithm (to a stationary solution) is guaranteed, and its effectiveness is demonstrated via extensive simulation.

The Multicell Multiuser MIMO Uplink with Very Large Antenna Arrays and a Finite-Dimensional Channel

We consider multicell multiuser MIMO systems with a very large number of antennas at the base station (BS). We assume that the channel is estimated by using uplink training. We further consider a physical channel model where the angular domain is separated into a finite number of distinct directions. We analyze the so-called pilot contamination effect discovered in previous work, and show that this effect persists under the finite-dimensional channel model that we consider. In particular, we consider a uniform array at the BS. For this scenario, we show that when the number of BS antennas goes to infinity, the system performance under a finite-dimensional channel model with P angular bins is the same as the performance under an uncorrelated channel model with P antennas. We further derive a lower bound on the achievable rate of uplink data transmission with a linear detector at the BS. We then specialize this lower bound to the cases of maximum-ratio combining (MRC) and zero-forcing (ZF) receivers, for a finite and an infinite number of BS antennas. Numerical results corroborate our analysis and show a comparison between the performances of MRC and ZF in terms of sum-rate.

A Precoding Scheme Based Game Theory for Cooperative MIMO System

This paper considers a tradeoff between maximizing the user’s signal interference noise ratio and minimizing interference leakage in preprocessing for multi-cell MIMO system. A sub-optimal precodingalgorithm based on game theory is proposed to deal with it. A game-based algorithm mathematics model is constructed and interference pricing function is also introduced in the solution to the precoding vector by Lagrange equation. Implement step of the proposed algorithm is also summarized in the paper. Finally in simulation the proposed algorithm is compared with conventional algorithms and convergence of utility function is also discussed. The simulation results show that the proposed algorithm provide improvement over existing schemes.

다중 셀 다중 안테나 하향링크 채널에서의 간섭 정렬 송수신기 설계

본 논문에서는 임의의 셀 수 혹은 셀 당 임의의 사용자 수를 가지는 다중 셀 다중 안테나 하향링크 채널에 적용 가능한 간섭 정렬 기반 송수신기 설계를 제안한다. 타 셀로부터 오는 간섭 신호를 유효 타 셀 간섭 채널로 정렬시키는 수신 빔포머를 설계한 후, 해당 기지국으로부터 야기되는 모든 간섭 신호를 제거할 수 있는 송신 프리코더를 설계한다. 제안된 송수신기 설계는 사용자 당 전송하는 데이터 스트림 수 만큼의 자유도를 획득할 수 있고 이를 위한 안테나 조건을 구한다. 모의 실험 결과를 통하여 기지국과 사용자의 안테나 수가 동일한 조건 하에서 제안된 송수신기 설계가 기존의 기법보다 높은 자유도를 얻음을 확인한다. In this paper, we propose a novel interference alignment transceiver for multi-cell MIMO downlink channels with arbitrary number of cells and users per cell. We design the receive beamformer to align the interference from undesired base stations to the effective inter-cell interference (ICI) channels. Subsequently, we design the transmit precoder which can nulllify the interference from the corresponding base station. The proposed transceiver design can attain the degrees of freedom (DOF) equal to the number of streams per user. Accordingly, we investigate conditions for the antenna configuration. From numerical results, we confirm that the proposed transceiver design can achieve higher DOF than the conventional scheme under equal antenna configuration.

Energy- and Cost-Efficient Mobile Communication Using Multi-Cell MIMO and Relaying

In this paper, relaying and multi-cell MIMO transmission are investigated as approaches for improving resource reuse and more flexible organization of cellular networks. The analysis focuses on approaches for future cellular systems, which jointly exploit relaying and multi-cell MIMO transmission. Possible candidate approaches are identified, simplified for practical applications and evaluated using a system-level model from the European research project WINNER. Their achievable throughput is analyzed under practical constraints using three different normalization approaches: cost-normalization, energy-normalization, and joint cost-energy-normalization. It can be shown that the combined approach of relaying and multi-cell MIMO provides significant gains for the uplink communication. The selected approach exploits cooperative multi-cell MIMO processing between base stations and relay nodes, and uses a resource coordination technique on the links between relay nodes and user terminals. If a relay-based deployment is subject to a cost- and energy-normalization, multi-cell MIMO outperforms relaying with respect to achievable downlink throughput.

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 systems. As the large number of users in the system and the limited number of simultaneously supportable users with MC-MU-MIMO, it is necessary to select a subset of users to maximize the total throughput. However, the fully centralized user selection algorithms used in single cell system, which will incur high complexity and backhaul load in multi-cell cooperative processing (MCP) systems, are not suitable to MC-MU-MIMO systems. This article presents a two cascaded user selection method for MCP systems with multi-cell block diagonalization. In this paper, a local optimal subset of users, which can maximize the local sum capacity, is first chosen by the greedy method in every cooperative base station in parallel. Then, all the cooperative base stations report their local optimal users to the central unit (CU). Finally, the global optimal users, which can maximize the global sum capacity of MCP systems, are selected from the aggregated local optimal users at the CU. The simulation results show that the proposed method performs closely to the optimal and centralized algorithm. Meanwhile, the complexity and backhaul load are reduced dramatically.

Multi-BS MIMO cooperation: challenges and practical solutions in 4G systems

Various multiple-input multiple-output techniques have been introduced to improve performance of next-generation systems. In single-cell environments, closed-loop MIMO schemes increase the system capacity as well as cell coverage. In cellular networks where interference coming from other cells is usually a dominant factor, several multiple-base-station cooperation schemes have been introduced to mitigate the intercell interference. In this article, we first provide an overview of scenarios and technology categories for multi-BS MIMO cooperation schemes. Next we introduce closed-loop multicell MIMO techniques adopted in IEEE 802.16m, which do not require data forwarding among different base stations. In particular, this article explains the overall operations which minimize overhead. We also present simulation results that confirm the efficiency of the presented interference mitigation method.

Multi-Cell MIMO Downlink With Cell Cooperation and Fair Scheduling: A Large-System Limit Analysis

We consider the downlink of a cellular network with multiple cells and multi-antenna base stations, including a realistic distance-dependent pathloss model, clusters of cooperating cells, and general "fairness" requirements. Beyond Monte Carlo simulation, no efficient computation method to evaluate the ergodic throughput of such systems has been presented so far. We propose an analytic solution based on the combination of large random matrix results and convex optimization. The proposed method is computationally much more efficient than Monte Carlo simulation and provides surprisingly accurate approximations for the actual finite-dimensional systems, even for a small number of users and base station antennas. Numerical examples include 2-cell linear and three-sectored 7-cell planar layouts, with no inter-cell cooperation, sector cooperation, or full inter-cell cooperation.

Distributed Probabilistic-Data-Association-Based Soft Reception Employing Base Station Cooperation in MIMO-Aided Multiuser Multicell Systems

Intercell cochannel interference (CCI) mitigation is investigated in the context of cellular systems relying on dense frequency reuse (FR). A distributed base-station (BS)-cooperation-aided soft reception scheme using the probabilistic data association (PDA) algorithm and soft combining (SC) is proposed for the uplink of multiuser multicell MIMO systems. The realistic 19-cell hexagonal cellular model relying on unity FR is considered, where both the BSs and the mobile stations (MSs) are equipped with multiple antennas. Local-cooperation-based message passing is used, instead of a global message passing chain for the sake of reducing the backhaul traffic. The PDA algorithm is employed as a low-complexity solution for producing soft information, which facilitates the employment of SC at the individual BSs to generate the final soft decision metric. Our simulations and analysis demonstrate that, despite its low additional complexity and backhaul traffic, the proposed distributed PDA-aided SC (DPDA-SC) reception scheme significantly outperforms the conventional noncooperative benchmarkers. Furthermore, since only the index of the possible discrete value of the quantized converged soft information has to be exchanged for SC in practice, the proposed DPDA-SC scheme is relatively robust to the quantization errors of the soft information exchanged. As a beneficial result, the backhaul traffic is dramatically reduced at negligible performance degradation.