Sub-channel shared resource allocation for multi-user distributed MIMO-OFDM systems

Well-controlled resource allocation is crucial for promoting the performance of multiple input multiple output orthogonal frequency division multiplexing (MIMO-OFDM) systems. Recent studies have focused primarily on traditional centralized systems or distributed antenna systems (DASs), and usually assumed that one sub-carrier or sub-channel is exclusively occupied by one user. To promote system performance, we propose a sub-channel shared resource allocation algorithm for multi-user distributed MIMO-OFDM systems. Each sub-channel can be shared by multiple users in the algorithm, which is different from previous algorithms. The algorithm assumes that each user communicates with only two best ports in the system. On each sub-carrier, it allocates a sub-channel in descending order, which means one sub-channel that can minimize signal to leakage plus noise ratio (SLNR) loss is deleted until the number of remaining sub-channels is equal to that of receiving antennas. If there are still sub-channels after all users are processed, these sub-channels will be allocated to users who can maximize the SLNR gain. Simulations show that compared to other algorithms, our proposed algorithm has better capacity performance and enables the system to provide service to more users under the same capacity constraints.

[1]  Liu Zhen Resource Allocation Based on MAS Coordination , 2006 .

[2]  B. Mielczarek,et al.  Throughput of realistic multi-user MIMO-OFDM systems , 2004, Eighth IEEE International Symposium on Spread Spectrum Techniques and Applications - Programme and Book of Abstracts (IEEE Cat. No.04TH8738).

[3]  Derrick Wing Kwan Ng,et al.  Energy-Efficient Resource Allocation in OFDMA Systems with Large Numbers of Base Station Antennas , 2012, IEEE Transactions on Wireless Communications.

[4]  Abdellah Ait Ouahman,et al.  A low complexity resources allocation algorithm based on the best subchannel for multiuser MIMO OFDM system , 2011, 2011 International Conference on Multimedia Computing and Systems.

[5]  Ali H. Sayed,et al.  A Leakage-Based Precoding Scheme for Downlink Multi-User MIMO Channels , 2007, IEEE Transactions on Wireless Communications.

[6]  Jiangzhou Wang,et al.  Radio Resource Allocation in Multiuser Distributed Antenna Systems , 2013, IEEE Journal on Selected Areas in Communications.

[7]  Na Lu,et al.  Downlink MIMO performance evaluation for LTE/LTE-A indoor distributed antenna systems , 2012, 2012 1st IEEE International Conference on Communications in China (ICCC).

[8]  Angela Doufexi,et al.  Reduced Complexity Joint User and Receive Antenna Selection Algorithms for SLNR-Based Precoding in MU-MIMO Systems , 2012, 2012 IEEE 75th Vehicular Technology Conference (VTC Spring).

[9]  Xiaohu You,et al.  Energy-Efficient Resource Allocation in OFDM Systems With Distributed Antennas , 2014, IEEE Transactions on Vehicular Technology.

[10]  Xiaohu You,et al.  Energy Efficient Comparison between Distributed MIMO and Co-Located MIMO in the Uplink Cellular Systems , 2012, 2012 IEEE Vehicular Technology Conference (VTC Fall).

[11]  Jing Liu,et al.  Leakage-based user scheduling in MU-MIMO broadcast channel , 2009, Science in China Series F: Information Sciences.

[12]  Shlomo Shamai,et al.  Distributed MIMO Systems for Nomadic Applications Over a Symmetric Interference Channel , 2009, IEEE Transactions on Information Theory.

[13]  Jie Chen,et al.  Applying Bargaining Solutions to Resource Allocation in Multiuser MIMO-OFDMA Broadcast Systems , 2012, IEEE Journal of Selected Topics in Signal Processing.

[14]  Derrick Wing Kwan Ng,et al.  Energy-Efficient Resource Allocation in OFDMA Systems with Large Numbers of Base Station Antennas , 2012, IEEE Trans. Wirel. Commun..

[15]  Ana I. Pérez-Neira,et al.  Efficient Margin Adaptive Scheduling for MIMO-OFDMA Systems , 2013, IEEE Transactions on Wireless Communications.

[16]  Wu Wei-ling,et al.  Fast Antenna Selection Algorithms for Distributed MIMO Systems , 2007 .