多用戶正交分頻多工(multiuser orthogonal frequency division multiplexing ， MU-OFDM)系統是一個非常有效率的傳輸技術，能有效的改善系統性能及增加頻譜使用效率。在多用戶正交分頻多工系統一個重要的問題是基地台如何根據使用者各自不同的通道特性，動態的分配子載波、位元及功率來增加系統的性能。傳統的子載波及位元分配演算法在分配子載波及位元是以載波為單位，這樣將會造成很高的計算複雜度。因此，已有其他文獻提出以鄰近子載波分區塊的方法來降低子載波及位元分配的計算複雜度，但是以此種方法所使用的平均訊雜比值來計算區塊內的位元及功率分配，將會造成非常嚴重的性能損耗。有別於傳統的子載波及位元分配演算法及區塊式子載波及位元分配演算法，我們提出了一種新的區塊式子載波及位元分配演算法來降低整個系統的計算複雜度及性能損耗。我們將此演算法分成兩個步驟：第一步，在區塊式子載波分配部份，我們根據所提出的通道增益值分類方法將子載波分群，目的是將通道增益值差不多的子載波分配到同一個區塊，來降低做區塊式位元及功率分配所造成的性能損耗；第二步，在區塊式位元及功率分配部份，我們也提出了一個根據最小平方誤差準則所求出的區塊式訊雜比值來降低整體的傳輸功率損失。
經由電腦模擬及複雜度比較，我們可以看出本篇論文所提出的區塊式子載波及位元分配演算法和根據最小平方誤差準則所求出的區塊式訊雜比值可以有效的降低計算複雜度及性能損耗。

Multiuser orthogonal frequency division multiplexing (MU-OFDM) is a promising technique for achieving high spectral efficiency in future wireless communication systems. A key issue in MU-OFDM system is the dynamic subcarrier, bit, and power allocation among users sharing the channel. Conventional subcarrier and bit allocation algorithms assign subcarriers and bits based on “subcarrier to subcarrier” mode. It will cause large computational complexity. Therefore, some papers have proposed a blockwise subcarrier and bit allocation algorithms based on adjacent subcarriers to reduce the computational complexity. But this kind of blockwise method will cause large performance degradation due to use the average SNR value to calculate blockwise bit and power allocation. Differ from these two subcarrier and bit allocation algorithms, we propose a novel blcokwise subcarrier and bit allocation algorithm to reduce the computational complexity and performance loss. We divide the proposed blockwise subcarrier and bit allocation algorithm into two steps: first, we bind the subcarriers to blocks based on the proposed channel level classification method; second, we also propose a novel signal-to-noise ratio (SNR) value based on least-squared (LS) criterion to reduce the performance loss caused by blockwise bit and power allocation,.
From the simulation results and complexity comparisons, the proposed blockwise subcarrier, bit, and power allocation algorithm with LS-SNR value can largely decrease the computational complexity and the performance loss.

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