针对格基约减辅助的THP(LRA-THP)算法运算复杂度高问题,在一种分组预编码算法的基础上,提出一种适用于多波束卫星系统的低复杂度分组预编码算法,该算法根据波束间的距离对用户进行分组,通过最大化SSLNR得到预处理矩阵,抑制组间干扰,各...针对格基约减辅助的THP(LRA-THP)算法运算复杂度高问题,在一种分组预编码算法的基础上,提出一种适用于多波束卫星系统的低复杂度分组预编码算法,该算法根据波束间的距离对用户进行分组,通过最大化SSLNR得到预处理矩阵,抑制组间干扰,各组内采用LRA-THP算法,计算预处理矩阵时充分利用多波束卫星信道的特点,降低需要求解的预处理矩阵的维度,从而减小算法的运算复杂度.理论及仿真分析结果显示,该算法的运算量远低于LRA-THP,与原分组预编码算法相比,该算法的复杂度能够降低24%,同时性能损失不超过0.1 d B.另外,该算法中引入一组参数,使其能够灵活地在复杂度与可靠性之间进行折中.展开更多
In this paper, the design of linear leakage-based precoders is considered for multiple-input multiple-output （MIMO） downlinks. Our proposed scheme minimizes total transmit power under each user＇s signal-to-leakage-...In this paper, the design of linear leakage-based precoders is considered for multiple-input multiple-output （MIMO） downlinks. Our proposed scheme minimizes total transmit power under each user＇s signal-to-leakage-plus-noise ratio （SLNR） constraint. When the base station knows perfect channel state information （CSI）, suitable reformulation of design problem allows the successful application of semidefinite relaxation （SDR） techniques. When the base station knows imperfect CSI with limited estimation errors, the design problem can be solved using semidefinite program （SDP）. At the same time, it can dynamically allocate each user＇s SLNR threshold according to each user＇s channel state, so it is more feasible than other similar S1NR-based precoding methods. Simulation results show that using large SLNR thresholds, the proposed design has better bit error rate （BER） performance than maximal-SLNR precoding method at high signal-to-noise ratio （SNR）. Moreover, when the base station knows imperfect channel state information, the proposed precoder is robust to channel estimation errors, and has better BER preformance than other similar SINR-based precoding methods.展开更多
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 tr...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 multiuser 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.展开更多
文摘针对格基约减辅助的THP(LRA-THP)算法运算复杂度高问题,在一种分组预编码算法的基础上,提出一种适用于多波束卫星系统的低复杂度分组预编码算法,该算法根据波束间的距离对用户进行分组,通过最大化SSLNR得到预处理矩阵,抑制组间干扰,各组内采用LRA-THP算法,计算预处理矩阵时充分利用多波束卫星信道的特点,降低需要求解的预处理矩阵的维度,从而减小算法的运算复杂度.理论及仿真分析结果显示,该算法的运算量远低于LRA-THP,与原分组预编码算法相比,该算法的复杂度能够降低24%,同时性能损失不超过0.1 d B.另外,该算法中引入一组参数,使其能够灵活地在复杂度与可靠性之间进行折中.
基金supported by the National Natural Science Foudation of China (60972046)the S&T Major Special Project (2009ZX03003-11-05, 2010ZX03003-003)the Scientific Research Program Funded by Shaanxi Provincial Education Commission (2010JK666)
文摘In this paper, the design of linear leakage-based precoders is considered for multiple-input multiple-output （MIMO） downlinks. Our proposed scheme minimizes total transmit power under each user＇s signal-to-leakage-plus-noise ratio （SLNR） constraint. When the base station knows perfect channel state information （CSI）, suitable reformulation of design problem allows the successful application of semidefinite relaxation （SDR） techniques. When the base station knows imperfect CSI with limited estimation errors, the design problem can be solved using semidefinite program （SDP）. At the same time, it can dynamically allocate each user＇s SLNR threshold according to each user＇s channel state, so it is more feasible than other similar S1NR-based precoding methods. Simulation results show that using large SLNR thresholds, the proposed design has better bit error rate （BER） performance than maximal-SLNR precoding method at high signal-to-noise ratio （SNR）. Moreover, when the base station knows imperfect channel state information, the proposed precoder is robust to channel estimation errors, and has better BER preformance than other similar SINR-based precoding methods.
基金Project supported by the National High-Tech R&D Program(863) of China(Nos.2012AA01A502 and 2012AA01A505)
文摘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 multiuser 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.
