A Dynamic Clustering and Resource Allocation Algorithm for Downlink CoMP Systems with Multiple Antenna UEs

Coordinated multi-point (CoMP) schemes have been widely studied in the recent years to tackle the inter-cell interference. In practice, latency and throughput constraints on the backhaul allow the organization of only small clusters of base stations (BSs) where joint processing (JP) can be implemented. In this work we focus on downlink CoMP-JP with multiple antenna user equipments (UEs) and propose a novel dynamic clustering algorithm. The additional degrees of freedom at the UE can be used to suppress the residual interference by using an interference rejection combiner (IRC) and allow a multistream transmission. In our proposal we first define a set of candidate clusters depending on long-term channel conditions. Then, in each time block, we develop a resource allocation scheme by jointly optimizing transmitter and receiver where: a) within each candidate cluster a weighted sum rate is estimated and then b) a set of clusters is scheduled in order to maximize the system weighted sum rate. Numerical results show that much higher rates are achieved when UEs are equipped with multiple antennas. Moreover, as this performance improvement is mainly due to the IRC, the gain achieved by the proposed approach with respect to the non-cooperative scheme decreases by increasing the number of UE antennas.Comment: 27 pages, 8 figure

Optimize Power Allocation Scheme to Maximize Sum Rate in CoMP with Limited Channel State Information

Extensive use of mobile applications throws many challenges in cellular systems like cell edge throughput, inter cell interference and spectral e�ciency. Many of these challenges have been resolved using Coordinated Multi-Point (CoMP), developed in the Third Generation Partnership Project for LTE-Advanced) to a great extent. CoMP cooperatively process signals from base sta- tions that are connected to various multiple terminals (user equipment (UEs)) at transmission and reception. This CoMP improves throughput, reduces or even removes inter-cell interference and increases spectral e�ciency in the downlink of multi-antenna coordinated multipoint systems. Many researchers addressed these issues assuming that BSs have the knowledge of the common control channels dedicated to all UEs and also about the full or partial channel state information (CSI) of all the links. From the CSI available at the BSs, multiuser interference can be managed at the BSs. To make this feasible, UEs are responsible for collecting downlink CSI. But, CSI measurement (instantaneous and/or statistical) is imperfect in nature because of the randomly varying nature of the channels at random times. These incorrect CSI values available at the BSs may, in turn, create multi-user interference. There are many techniques to suppress the multi-user interference, among which the feedback scheme is the one which is gaining a lot of attention. In feedback schemes, CSI information needs to be fed back to the base station from UEs in the uplink. It is obvious, the question arises on the type and amount of feedback need to be used. Research has been progressing in this front and some feedback techniques have been proposed. Three basic CoMP Feedback schemes are available. Explicit or statistical channel information feedback scheme in which channel information like channels's covariance matrix of the channel are shared between the transmitter and receiver. Next, implicit or statistical channel information feedback which contains information such as Channel quality indication or Precoding matrix indicator or Rank indicator. 1st applied to TDD LTE type structure and 2nd of feedback scheme can be applied in the FDD system. Finally, we have UE which tranmit the sounding reference signal (CSI). This type of feedback scheme is applied to exploit channel reciprocity and to reduce channel intercell interference and this can be applied in the TDD system. We have analyzed the scenario of LTE TDD based system. After this, optimization of power is also required because users at the cell edge required more attention than the user locating at the center of the cell. In my work, it shows estimated power gives exponential divercity for high SNR as low SNR too. In this method, a compression feedback method is analyzed to provide multi-cell spatial channel information. It improves the feedback e�ciency and throughput. The rows and columns of the channel matrix are compressed using Eigenmode of the user and codebook based scheme speci�ed in LTE speci�cation. The main drawback of this scheme is that spectral e�ciency is achieved with the cost of increased overheads for feedback and evolved NodeB (eNB). Other factor is complexity of eNodeB which is to be addressed in future work

Optimality Properties, Distributed Strategies, and Measurement-Based Evaluation of Coordinated Multicell OFDMA Transmission

The throughput of multicell systems is inherently limited by interference and the available communication resources. Coordinated resource allocation is the key to efficient performance, but the demand on backhaul signaling and computational resources grows rapidly with number of cells, terminals, and subcarriers. To handle this, we propose a novel multicell framework with dynamic cooperation clusters where each terminal is jointly served by a small set of base stations. Each base station coordinates interference to neighboring terminals only, thus limiting backhaul signalling and making the framework scalable. This framework can describe anything from interference channels to ideal joint multicell transmission. The resource allocation (i.e., precoding and scheduling) is formulated as an optimization problem (P1) with performance described by arbitrary monotonic functions of the signal-to-interference-and-noise ratios (SINRs) and arbitrary linear power constraints. Although (P1) is non-convex and difficult to solve optimally, we are able to prove: 1) Optimality of single-stream beamforming; 2) Conditions for full power usage; and 3) A precoding parametrization based on a few parameters between zero and one. These optimality properties are used to propose low-complexity strategies: both a centralized scheme and a distributed version that only requires local channel knowledge and processing. We evaluate the performance on measured multicell channels and observe that the proposed strategies achieve close-to-optimal performance among centralized and distributed solutions, respectively. In addition, we show that multicell interference coordination can give substantial improvements in sum performance, but that joint transmission is very sensitive to synchronization errors and that some terminals can experience performance degradations.Comment: Published in IEEE Transactions on Signal Processing, 15 pages, 7 figures. This version corrects typos related to Eq. (4) and Eq. (28