Search - mimo sinr

Search - mimo sinr - List

[matlab] SMI(Algorithm) DL : 0: 智能天线自适应非盲波束形成SMI算法，有很好的参考价值。-Smart Antenna Adaptive SMI non-blind beamforming algorithms, have a good reference value.
Update : 2025-03-07 Size : 2kb Publisher : 刘秦
[Documents] Ergodic_Capacity_of_LTE_Downlink_Multiuser_MIMO_Sy DL : 0: 本文推导了MIMO系统，在频域分组调度准则下，SINR分布函数的表达式，以及平均信道容量。-The paper contributions are the derivation of a mathematical expression of the SINR distribution and the average channel capacity for multiuser MIMO systems with a frequency domain packet scheduler.
Update : 2025-03-07 Size : 124kb Publisher : lina
[SCM] 14.pdf.tar DL : 0: Abstract—2×2 unitary precoding based on receiver feedback is applied alongside spatial multiplexing at the base station in HSDPA (D-TxAA) when the mobile terminal supports MIMO transmissios [1]. This precoding will influence achievable sumrate of the MIMO channel if it influences the Signal-to- Interference-plus-Noise Ratio (SINR) of streams at the receiver (RX) output. We propose a set of MIMO HSDPA receivers, all based upon a LMMSE chip-level matrix filter (equalizer) front end, and introduce the notion of joint bias for the MIMO chip equalizer. Statistical properties of the spatial model thus obtained are exploited to analyze the performance of proposed MIMO receivers. It is shown that precoding choice depends upon the MIMO receiver and the extent of its impact depends on the MIMO RX.
Update : 2025-03-07 Size : 191kb Publisher : ashish
[matlab] Untitled7 DL : 0: mimo radar SINR plot vs doppler frequency-mimo radar SINR plot vs doppler frequency
Update : 2025-03-07 Size : 1kb Publisher : vijay
[matlab] MIMO_OFDM_Sys_for_downlink_freq DL : 0: Analysis of frequency and channel estimator for down link of MIMO OFDM system-The analysis should be done based on MATLAB codes, which includes parameters like SNR, SINR
Update : 2025-03-07 Size : 425kb Publisher : 崽崽
[Other] mimo-scheduling DL : 0: We present a user-scheduling scheme for multiuser multiple-input–multiple-output (MIMO) systems with random unitary beamforming (RUB) in this paper. The new scheme, which is termed as adaptive beam activation based on the conditional best beam index feedback (ABA-CBBI), requires low average feedback load by imposing a feedback threshold on the users’ signal-to-interference-plus-noise ratio (SINR) and suffers less multiuser interference by only activating those beams requested by at least one user.
Update : 2025-03-07 Size : 11.83mb Publisher : diwakar pandey
[SMS] Aprox_MU_MIMO_Q_model DL : 0: The model is built upon the assumption that the probabil- ity distribution of available destinations among the buered frames at the Base Station (BS) is approximately the same as the probability distribution of the trac arriving to the BS, this is, the amount of trac directed to each MN with respect to the total trac load. This assumption leads to a simple, but accurate, queueing model for Multi- user MIMO systems that accounts for the impact of a nite number of active MNs in non-saturated conditions. The model is easily applicable to any Multi-user MIMO scenario given that the probability density function of the post-processing SINR (Signal to Interference and Noise Ratio) for each MN is known.
Update : 2025-03-07 Size : 90kb Publisher : ImranKhan
[matlab] K_user_IC DL : 0: k用户MIMO干扰信道干扰对齐算法。包括最小干扰泄露算法，最大信干噪比算法，秩约束秩最小化算法-k-user MIMO interference channel interference alignment algorithm. Including a minimum interference leakage algorithm, the maximum SINR algorithm, constrained rank rank minimization algorithm
Update : 2025-03-07 Size : 8kb Publisher : linjingjing
[Program doc] 07227112 DL : 0: Thanks to the small wavelength at millimeter wave (mmWave) frequency, it is promising to combine massive multiple-input and multiple-output (MIMO) with mmWave. MmWave massive MIMO will differ the conventional massive MIMO, due to the differences in propagation and hardware constraints. This paper proposes a stochastic geometry framework for uating the performance in large-scale mmWave massive MIMO networks. Based on the system model, analytical expressions are provided for the asymptotic signal-tointerference- plus-noise ratio (SINR) distributions in both uplink and downlink, when the number of base station antennas goes to infinity. Numerical results indicate a fast convergence in the SINR distribution to its asymptotic equivalence in dense mmWave networks. A comparison with conventional massive MIMO shows that mmWave massive MIMO achieves a higher cell throughput with sufficiently dense deployments.-Thanks to the small wavelength at millimeter wave (mmWave) frequency, it is promising to combine massive multiple-input and multiple-output (MIMO) with mmWave. MmWave massive MIMO will differ the conventional massive MIMO, due to the differences in propagation and hardware constraints. This paper proposes a stochastic geometry framework for uating the performance in large-scale mmWave massive MIMO networks. Based on the system model, analytical expressions are provided for the asymptotic signal-tointerference- plus-noise ratio (SINR) distributions in both uplink and downlink, when the number of base station antennas goes to infinity. Numerical results indicate a fast convergence in the SINR distribution to its asymptotic equivalence in dense mmWave networks. A comparison with conventional massive MIMO shows that mmWave massive MIMO achieves a higher cell throughput with sufficiently dense deployments.
Update : 2025-03-07 Size : 184kb Publisher : hadjidw
[matlab] On transceiver design and channel quantization for downlink multiuser MIMO systems with limited feedback DL : 0: MESC is a procedure to select the codeword and receive combining vector jointly to maximize an SINR-like metric.
Update : 2017-09-18 Size : 29.77kb Publisher : mohanad84