Multi-cell Cooperative Transmission Research Articles

Resource Allocation for Cooperative Transmission in Optical Wireless Cellular Networks With Illumination Requirements

Visible light communication (VLC) often suffers from line-of-sight path blockages and high levels of inter-cell interference. Thus, the analysis and design of cooperation techniques become crucial to address these key impairments. This paper studies the performance of different resource allocation schemes that are suitable for multi-cell cooperative transmission when tri- and tetra-chromatic light-emitting diodes (LEDs) and optical orthogonal frequency-division multiple access are utilized. Firstly, guidelines are derived for maintaining the same spatial distribution of the signal-to-interference-plus-noise ratio (SINR) in every sector of the multi-cell environment in case of stand-alone (non-cooperative) and cooperative transmission. Secondly, the possible resource allocation configurations for both stand-alone and cooperative transmission modes are identified for different LED types and available orthogonal resources (i.e., frequency sub-bands per color and sectors per cell). Finally, the data rate gain of the multiple resource allocation configurations are also analyzed, while verifying the illumination constraints. The obtained results confirm that the proper design of cooperative transmission configurations will be of paramount importance to provide reliable wireless link in ultra-dense VLC deployments.

Weighted MMSE Precoder Designs for Sum-Utility Maximization in Multi-User SWIPT Network-MIMO With Per-BS Power Constraints

Simultaneous wireless information and power transfer (SWIPT) is a promising technique to transfer information and energy signals at the same time and frequency utilizing the multi-input multi-output (MIMO) beamforming. In this correspondence, the SWIPT MIMO technique is realized in the multicell cooperative transmission environment, namely, network-MIMO where the signals from different base-stations (BSs) to all the mobile users can be jointly designed based on the perfect knowledge of the downlink channels and transmit messages. To develop an efficient precoding matrix, we adopt the weighted minimum mean squared error criterion that can be generally applied to the sum-utility maximization of each receiver's information rate. In the SWIPT network-MIMO, a number of constraints arise including the power constraint at each BS, namely, the per-BS power constraints and the energy constraint at the energy harvesting users, which makes the problem challenging. A main contribution of the paper is to propose a simple bisection-based algorithm that finds a solution. The efficiency of the proposed algorithm is verified via computer simulation results.

Beam interference suppression in multi-cell millimeter wave communications

Due to the increase in the number of users, beam switching is used for suppressing interference, which leads to higher computational complexity in multi-cell millimeter wave communications. In order to resolve this problem, a beam interference model is introduced, and a lower complexity beam interference suppression algorithm based on user grouping is proposed. The proposed algorithm operates beam switching and multi-cell cooperative transmission for a part of the users when there exists beam interference due to high user density. In particular, considering the distinct interference suffered by each user, the proposed dual-threshold user grouping method can effectively solve the frequent switching problem at the base station caused by multi-cell cooperative transmission in multi-cell environments. Simulation results show that the proposed algorithm can reduce the computational complexity of beam switching and approach ideal system capacity, compared with conventional interference suppression algorithms that do not involve grouping of users.

Energy Efficient Clustering and Beamforming for Cloud Radio Access Networks

Cloud radio access network (Cloud-RAN) is recognized as one of the key enabling techniques for 5G due to its advantages in flexibility. In addition, the greatly increased energy efficiency (EE, evaluated by bits/Hz/J) is listed as one main objective when designing 5G wireless network. In this paper, we concentrate on EE optimization through Cloud-RAN enabled flexible multicell cooperative transmission. A joint clustering and beamforming problem for EE optimization is formulated. Due to the combinatorial nature of the clustering process and the non-convexity of the energy efficient beamforming design, the problem is difficult to solve directly. Therefore, we propose a hierarchical iterative framework to solve the problem. The origin optimization problem is decoupled into two subproblems, i.e., energy efficient beamforming problem and energy efficient cluster forming problem. Coalition formation game theory and fractional programming are utilized to obtain the optimal network cluster partition and beamformers respectively. Simulation results demonstrate the superior performance of the proposed algorithms.

MVDR-Based Multicell Cooperative Beamforming Techniques for Unicast/Multicast MIMO Networks With Perfect/Imperfect CSI

In this paper, we consider unicast/multicast multicell cooperative transmission with interference among users/user groups. In this context, we derive the optimal minimum variance distortionless response (MVDR)-based successive minimum variance beamforming (SMVB) scheme that achieves a superior sum-rate performance compared with the block diagonalization scheme. Subsequently, we derive an optimal joint power allocation and broadcast beamforming scheme for multicell cooperative broadcast transmission for a pooled power constraint at the base stations. This scheme is extended to include per base station power constraints by formulating it as a relaxed semi-definite program (SDP). We also consider the multicell cooperative uplink scenario and derive a successive multiuser (MU) uplink beamforming (SMUB) scheme that maximizes the signal-to-interference-plus-noise ratio (SINR) of each user. Next, we consider imperfect channel state information (CSI) and derive a robust beamforming scheme for the downlink, based on minimizing the worst-case interference by formulating it as a second-order cone program. It is demonstrated that the corresponding robust beamformer for the uplink transmission can be derived by employing the multidimensional covariance fitting approach. Simulation results are presented to demonstrate the superior sum-rate performance of the proposed multicell transmission schemes. The performance is also compared with several bounds for cooperative multicell scenarios.

On channel quantization for multi-cell cooperative systems with limited feedback

Coherent multi-cell cooperative transmission, also referred to as coordinated multi-point transmission (CoMP), is a promising strategy to provide high spectral efficiency for universal frequency reuse cellular systems. To report the required channel information to the transmitter in frequency division duplexing systems, limited feedback techniques are often applied. Considering that the average channel gains from multiple base stations (BSs) to one mobile station are different and the number of cooperative BSs may be dynamic, it is neither flexible nor compatible to employ a large codebook to directly quantize the CoMP channel. In this paper, we employ per-cell codebooks for quantizing local and cross channels. We first propose a codeword selection criterion, aiming at maximizing an estimated data rate for each user. The proposed criterion can be applied for an arbitrary number of receive antennas at each user and also for an arbitrary number of data streams transmitted to each user. Considering that the resulting optimal per-cell codeword selection for CoMP channel is of high complexity, we propose a serial codeword selection method that has low complexity but yields comparable performance to that of the optimal codeword selection. We evaluate the proposed codeword selection criterion and method using measured CoMP channels from an urban environment as well as simulations. The results demonstrate significant performance gain as compared to an existing low-complexity method.

Multi-cell cooperative transmission based on unitary space-time modulation

As a non-coherent transmission scheme that does not require channel state information at both transmitters and receivers, unitary space-time modulation is a promising technique that can be applied in high mobility scenario where the fading coefficients are changing too fast to be tracked and estimated. This article proposes a multi-cell cooperative transmission scheme based on unitary space-time modulation. Each cooperative base-station transmits an individual unitary signal from the common constellation set to the mobile unit which is located at the cell edge and suffers from severe inter-cell interference. Compared with traditional unitary space-time modulation, cooperation among multi-cells not only eliminates the inter-cell co-channel interference but also increases the transmission rate by expanding the constellation size. Performance of error probability is analyzed for the proposed scenario with maximum-likelihood decoding, in which the exact pairwise error probability is derived. Additionally, constellation optimization for cooperative transmission is also discussed to achieve the balance between transmission efficiency and reliability. Simulation results are provided to confirm the effectiveness of the proposed scheme in both block-fading channels and fast-fading channels.

A linear precoding strategy based on particle swarm optimization in multicell cooperative transmission

An optimal linear precoding scheme based on Particle Swarm Optimization (PSO), which aims to maximize the system capacity of the cooperative transmission in the downlink channel, is proposed for a multicell multiuser single input single output system. With such a scheme, the optimal precoding vector could be easily searched for each user according to a simplified objective function. Simulation results show that the proposed scheme can obtain larger average spectrum efficiency and a better Bit Error Rate (BER) performance than Zero Forcing (ZF) and Minimum Mean Square Error (MMSE) algorithm.

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.