Coordinated Scheduling/beamforming Research Articles

Biclustering of Gene Expression Data Using Cuckoo Search and Genetic Algorithm

Biclustering analysis of gene expression data can reveal a large number of biologically significant local gene expression patterns. Therefore, a large number of biclustering algorithms apply meta-heuristic algorithms such as genetic algorithm (GA) and cuckoo search (CS) to analyze the biclusters. However, different meta-heuristic algorithms have different applicability and characteristics. For example, the CS algorithm can obtain high-quality bicluster and strong global search ability, but its local search ability is relatively poor. In contrast to the CS algorithm, the GA has strong local search ability, but its global search ability is poor. In order to not only improve the global search ability of a bicluster and its coverage, but also improve the local search ability of the bicluster and its quality, this paper proposed a meta-heuristic algorithm based on GA and CS algorithm (GA-CS Biclustering, Georgia Association of Community Service Boards (GACSB)) to solve the problem of gene expression data clustering. The algorithm uses the CS algorithm as the main framework, and uses the tournament strategy and the elite retention strategy based on the GA to generate the next generation of the population. Compared with the experimental results of common biclustering analysis algorithms such as correlated correspondence (CC), fast, local clustering (FLOC), interior search algorithm (ISA), Securities Exchange Board of India (SEBI), sum of squares between (SSB) and coordinated scheduling/beamforming (CSB), the GACSB algorithm can not only obtain biclusters of high quality, but also obtain biclusters of high-biologic significance. In addition, we also use different bicluster evaluation indicators, such as Average Correlation Value (ACV), Mean-Squared Residue (MSR) and Virtual Error (VE), and verify that the GACSB algorithm has a strong scalability.

Performance Analysis of CoMP in Ultra-Dense Networks with Limited Backhaul Capacity

Coordinated multipoint (CoMP) transmission provides an effective way to mitigate inter-cell interference as well as improve network performance in ultra-dense networks (UDNs). However, applying coordination among access points (APs) requires high backhaul capacity (BC), which becomes a bottleneck for employing CoMP. Considering a downlink UDN with limited BC, this paper conducts performance analysis of two CoMP schemes including joint transmission (JT) and coordinated scheduling/beamforming (CS/CB) from three aspects: a typical user's perspective, a typical AP's perspective and a network perspective. Firstly, the coverage probability (CP) and ergodic capacity (EC) of a typical user are characterized. Secondly, per-AP backhaul consumption is explicitly quantified and the successful serving probability (SSP) of a typical AP is proposed to capture its robustness to limited BC. Additionally, we propound effective ergodic capacity (EEC) to consider performance gain and backhaul consumption simultaneously from a global perspective. Further, the approximated expressions of all the performance metrics are given so that the impact of cluster size and AP density can be overtly observed. Numerical results illustrate that JT outperforms CS/CB in the case of high BC threshold, small cluster size or high AP density and a comparative smaller size is preferable for both two schemes for practice.

Multicell Coordinated Scheduling With Multiuser Zero-Forcing Beamforming

Coordinated scheduling/beamforming (CS/CB) is a cost-effective coordinated multipoint (CoMP) transmission paradigm that has been incorporated in the recent long-term evolution cellular standard. In this paper, we study CS/CB with the aim of developing low-complexity multicell coordinated user scheduling policies. We focus on a class of multicell interfering broadcast networks in which base stations have only local data and local channel state information, but each has sufficient antennas to serve multiple users using zero-forcing beamforming. The coordination problem is formulated as finding scheduling decisions across the cells such that the network sum rate is maximized. Starting from the two-cell model, we uncover the structure for a good scheduling decision, which in turn leads to the definition of two distributed scheduling policies of differing complexity and intercell coordination. Asymptotic theoretical bounds on the average sum rate are derived to predict the performance of the policies proposed. We extend to some example networks containing more than two cells and develop network-wide coordination policies. Numerical results confirm the effectiveness of the proposed policies and shed light on practical coordinated system design.

A Low-Complexity Cross-Layer Algorithm for Coordinated Downlink Scheduling and Robust Beamforming Under a Limited Feedback Constraint

Coordinated scheduling/beamforming (CS/CB) substantially mitigates the intercell interference (ICI), hence increasing the cell-edge throughput on the downlink (DL) of coordinated multipoint (CoMP) systems. To maximize the DL throughput, the cooperating base stations (BSs) jointly select the best set of users for DL scheduling and then jointly design a set of beamforming (BF) vectors to approach the throughput limit. However, finding the optimal BF vectors requires an exhaustive search and substantial channel state information (CSI) feedback, hence resulting in high algorithmic complexity and heavy uplink traffic load. Hence, we conceive a new cross-layer algorithm to achieve high performance at a lower feedback amount and at lower algorithmic complexity. Based on the fact that different BSs usually have different traffic loads, we divide the BSs into two different types, i.e., the master BSs (MBSs) and the slave BSs (SBSs), where MBSs have a higher transmission priority than SBSs. The scheduling relies on an interference threshold, whereas our robust BF scheme exploits both the channel direction information (CDI), which is quantized using the technique of limited feedback, and the channel quality information (CQI), which is assumed to be fed back accurately. Our numerical results show that the proposed algorithm does not lose much performance compared with that achieved by an exhaustive search, whereas the algorithmic complexity is as low as that of the solutions operating without CoMP.

Three novel opportunistic scheduling algorithms in CoMP-CSB scenario

Coordinated scheduling/beamforming (CSB), which belongs to the coordinated multi-point (CoMP) transmission, has received lots of attention recently due to its great potential to mitigate inter-cell interference (ICI) and to increase the cell-edge throughput, and meanwhile it only requires limited base station cooperation and is easy to implement. However, to the best of our knowledge, there are no effective scheduling algorithms with low complexity and overhead in CoMP-CSB scenario as yet. Thus, in this paper, we propose three novel opportunistic scheduling algorithms in CoMP-CSB scenario. All of them jointly consider the intended channel condition of the scheduled user from its serving cell and the orthogonality between the intended channel and the corresponding interference channels to concurrently scheduled users in nearby cells, thus exploiting multi-user diversity (MUD) and mitigating ICI at the same time. Algorithm 1 cooperatively chooses the most orthogonal user pair within a candidate user set in which all users have a large local channel feedback, while Algorithm 2 concurrently schedules the user pair with the largest ratio between the local channel feedbacks and the aforementioned orthogonality within the same candidate user set. Algorithm 3 performs in the way similar to the proportional fairness scheduling, while making a proper modification for its usage in CoMP-CSB scenario. The performance of the proposed scheduling algorithms are evaluated through simulation. Results show that, they all can significantly enhance the received signal to interference plus noise ratio (SINR) with relatively good fairness guarantee, thus achieving larger throughputs and utilities than several well-known scheduling algorithms. Algorithm 2 even outperforms Algorithm 1 when the aforementioned candidate user set is big enough in size and has a bit more overhead/complexity. Furthermore, Algorithms 3 is the best one among all the three proposed algorithms, but it requires more overhead/complexity than Algorithm 1 and 2. Finally, we give the optimal parameter for all of the three proposed algorithms, which can make a good tradeoff between performance and overhead/complexity.

MIMO 프리코딩을 고려한 셀 탐색 기법

CS/CB(Coordinated Scheduling/Beamforming) 방식은 인접 기지국으로부터의 간섭신호를 최소화시키는 MIMO(Multiple Input Multiple Output) 프리코더를 선택함으로써 셀 경계 사용자의 수율을 증가시킨다. 그러나 현재의 LTE(Long Term Evolution) 시스템에서는 안테나 한 개를 사용하여 주위 기지국으로부터 전송된 동기신호와 기준신호를 사용하여 초기화 단계에서 서빙 셀이 선택된다. 이와 같이 선택된 셀은 초기화 단계에서 MIMO 프리코더 이득을 고려하지 않고 선택되었기 때문에 데이터 전송시 최적의 선택이 아닐 수 있다. 본 논문에서는 MIMO 프리코더를 갖는 LTE 시스템을 위하여 초기화 단계에서 프리코더의 영향을 고려하여 셀을 선택하는 기법을 제안한다. 제안된 기법은 후보 기지국들에서 전송한 기준신호를 사용하여 획득한 정보(랭크, 유효 채널 용량, 유효 SINR(Signal to Interference plus Noise Ratio))를 사용하여 셀 경계의 단말이 서빙 기지국을 선택할 수 있도록 한다. 제안한 기법은 기존의 기법과 비교하여 다중 셀 환경하의 LTE 시스템에서 채널 용량을 크게 향상시킬 수 있음을 모의실험을 통하여 확인한다. In the CS/CB(Coordinated Scheduling/Beamforming) scheme, the cell edge user throughput is increased by selecting MIMO (Multiple Input Multiple Output) precoders which can minimize the interferences from adjacent base stations (BSs). However, in current LTE(Long Term Evolution) systems, the serving cell is selected in the initialization stage by using the synchronization signals and cell specific reference signals transmitted by adjacent BSs with a single antenna. The selected BS in the initialization stage may not be the best one since the MIMO precoding gain has not been considered in the cell selection stage. In this paper, a new cell selection technique is proposed for LTE systems with MIMO precoder by taking into account the effect of the precoder in the initialization stage. The proposed technique enables a user equipment (UE) in the cell boundary to select the serving BS by using the information (channel rank, effective channel capacity, and effective SINR(Signal to Interference plus Noise Ratio)) acquired from cell specific reference signals of candidate BSs. It is verified by computer simulation that the proposed technique can increase the channel capacity significantly in the multi-cell environments, compared with the conventional CS/CB scheme.