正交分頻多工是現今一種相當有潛力的無線網路傳輸技術，搭配多天線傳送訊號至目的端來形成一個分散式天線陣列，進而提供空間分集增益，透過已知的通道訊息來做適當的資源分配，將能有效提升系統的整體效能。在本論文中，我們考慮在正交分頻多工系統中的多輸入單輸出網路，並在此機制上做資源分配讓系統達到最佳的傳輸率。此最佳化問題包含了功率分配與子載波天線選擇，其中功率控制的問題除了考慮在總功率的限制下，也考慮了單根天線的功率上限。由於聯合功率控制與子載波天線選擇是一個混合整數規劃問題，因此我們提出以混合型基因演算法來解決此問題。並為了子載波天線選擇提出了二維的基因演算法，使基因演算法能更容易在我們的問題上收斂，更快得到較好的結果。基於當子載波數目與天線數目越大時，基因演算法較難收斂，我們亦提出了一個兩階段式低複雜度演算法，其在第一階段，先固定功率並使用基因演算法來求得子載波天線選擇對，而在第二
階段，則將子載波天線選擇對代入問題，並求得最佳功率分配。
在第二部分中我們考慮在多使用者的正交分頻多工系統中，結合子載波為區塊來考慮，並結合使用者選擇及區塊之天線選擇與功率控制，在於如何選擇區塊來使系統總傳輸速率最大化，對此複雜的非線性問題，我們亦使用二維的基因演算法來求解。
相關模擬結果顯示在不同的限制考量下，我們所提出之演算法相較於前人的方法，能獲得更好的系統效能。

Orthogonal frequency division multiplexing (OFDM) is an emerging transmission technique in wireless networks. Meanwhile, when the transmitter is equipped, with multiple antennas, the spatial diversity gains can enhance the performance. It is also known that proper resource allocation can increase the system efficacy.
In light of this, in this thesis, we consider the resource allocation in multi-input single-output OFDM networks. Our objective is to maximize the sum rate by per-subcarrier antenna selection and power control under the total power and the individual power of antenna. Such a joint consideration leads to a mixed integer programming (MIP) problem, which calls for enormous amount of complexity.
To resolve this MIP problem with reasonable cost, we address a heterogeneous two-dimensional (2-D) genetic algorithm (HGA). Furthermore, in light of the low convergence of HGA when the number of subcarriers and antennas are large, a two-stage low-complexity solution of the HGA is presented, which first uses the GA to determine the subcarrier-antenna pairs with equal power allocation and then devises the optimal power allocation in the second stage.
To reduce the overall complexity, we also consider in a chunk-based multiuser OFDM systems, and determine the optimum per-chunk antenna selection and power allocation with user selection so as to maximize the sum rate. Again, we devise a 2-D HGA to resolve the MIP involved.
Simulations show that the proposed new HGA approach and the suboptimal two-stage solutions provide superior performance compared with previous works. The
two-stage solutions are in particular appealing with greatly reduced computations.

[1] R. Freeman, Mobile Communications: Cellular Radio and Personal Communication
Services. Wiley-IEEE Press, 2007.
[2] B. E. Biglieri, MIMO Wireless Commun. Cambridge University Press, 2007.
[3] K. J. R. Liu, A. K, W. S. Sadek, and A. Kwasinski,Cooperative Commun. and
Networking. Cambridge University Press, 2008.
[4] B. Rankov and A. Wittneben, “Spectral efficient protocols for halfduplex
fading relay channels,” IEEE Journal on Selected Areas in Commun. , vol.
25, no. 2, pp. 379-389, Feb. 2007.
[5] T.Weiss, J. Hillenbrand, A. Krohn and F. K. Jondral, “Mutual interference in
OFDM-based spectrum pooling systems,”in Proc. IEEE Vehicular Technol.
Conf., vol. 4, pp. 1873-1877, 2004.
[6] T. Weiss and F. K. Jondral, “Spectrum pooling: an innovative strategy for
the enhancement of spectrum efficiency,” IEEE Commun. Magazine, vol. 42,
no. 3, pp. 8-14, Mar. 2004.
[7] A. Sendonaris, E. Erkip, and B. Aazhang, “User cooperation diversity-part I:
system description” and ”User cooperation diversity-part II: implementation
aspects and performance analysis,” IEEE Trans. Commun., vol. 51, no. 11,
pp. 1927-1938, 1939-1948, Nov. 2003.
[8] A. Paulraj, R. Nabar, D. Gore,Introduction to Space-Time Wireless Commun.
Cambridge University Press, 2003.
[9] M. Sandell and J. Coon, “Per-subcarrier antenna selection with power constraints
in OFDM systems,” IEEE Trans. Wireless Commun., vol. 8, no. 2,
pp. 673-677, Feb. 2009.
[10] C. Vithanage, J. Coon, and S. Parker, “On capacity-optimal precoding for
multiple-antenna systems subject to EIRP restrictions,” IEEE Trans. Wireless
Commun., vol. 7, no. 12, pp. 5182-5187, Mar. 2008.
[11] H. Shi, M. Katayama, T. Yamazato, H. Okada, and A. Ogawa, “An adaptive
antenna selection scheme for transmit diversity in OFDM systems,” in Proc.
IEEE Vehic. Technol. Conf., vol. 4, pp. 2168–2172, Oct. 2001.
[12] N. P. Le, L. C. Tran, F. Safaei, “Transmit antenna subset selection with power
balancing for high data rate MIMO-OFDM UWB systems,” in Proc. IEEE
International Conf. on Ultra-Wideband (ICUWB)., pp. 159-164 2013.
[13] K.-H. Park , Y.-C. Ko and M.-S. Alouini “Low-complexity transmission antenna
selection with power balancing in OFDM systems,” IEEE Trans. Wireless
Commun., vol. 9, no. 10, pp. 3018 -3023, 2010.
[14] R. Cepeda, J.P. Coon, “PAPR reduction by nulled subcarrier distortion in
per-subcarrier antenna selection systems,” in Proc. IEEE Wireless and Mobile
Computing, Networking and Commun. Conf., pp. 570 - 574. 2010.
[15] C.M. Vithanage, M. Sandell, J.P. Coon, Wang Yue “Precoding in OFDMbased
multi-antenna ultra-wideband systems,” IEEE Commun. Magazine.,
vol. 47, issue: 1, pp. 41 - 47, Jan. 2009.
[16] C.-T. Su and C.-S. Lee, “Network reconfiguration of distribution systems using
improved mixed-integer hybrid differential evolution,” IEEE Trans. Power
Delivery, vol. 18, no. 3, pp. 1022-1027, July 2003.
[17] I. G. Damousis, A. G. Bakirtzis and P. S. Dokopoulos, “A solution to the unitcommitment
problem using integer-coded genetic algorithm,” IEEE Trans.
Power Systems, vol. 19, no. 2, pp. 1165-1172, May 2004.
[18] J.H. Holland, Genetic Algorithms. Sci. Am. 1992.
[19] T. Yalcinoz and H. Altum, “Power economic dispatch using a hybrid genetic
algorithm,” IEEE Power Eng. Rev., vol. 21, pp. 59-60, 2001.
[20] H.-Y. Lu and W.-H. Fang, “Joint transmit/receive antenna selection in MIMO
systems based on the priority-based genetic algorithm,” IEEE Antennas and
Wireless Propagation Letters, vol. 6, pp. 588-591, 2007.
[21] K. Tang, K. Man, S. Kwong, and Q. He, “Genetic algorithms and their applications,”
IEEE Sig. Proc. Magazine, vol. 13, pp. 22-37, Nov. 1996.
[22] W. Yu and T. Lan, “Transmitter optimization for the multi-antenna downlink
with per-antenna power constraints,” IEEE Trans. Signal Proc., vol. 55, no.
6, pp. 2646-2660, Jun. 2007.
[23] L. Lei, V. Angelakis, and D. Yuan, “Performance Analysis of Chunk-Based
Resource Allocation in Wireless OFDMA Systems,” in Proc. IEEE Computer
Aided Modeling and Design of Communication Links and Networks Conf., pp.
90-94, 2012.
[24] D. Vasileios Papoutsis and A. Kotsopoulos, “Resource Allocation Algorithm
for MISO-OFDMA Systems with QoS Provisioning,” in Proc. International
Conf. on Wireless and Mobile Commun., pp. 7-11. 2011.
[25] I. Basturk and B. Ozbek, “Fairness aware resource allocation for downlink
MISO-OFDMA systems,” in Proc Wireless Commun. and Networking Conf.,
pp. 188-192. 2012.
[26] M. M. Selim , S. E. and H. Shalaby, “Reduced complexity QoS aware resource
allocation technique for MISO-OFDMA systems,” in Proc Computing,
Networking and Commun. Conf., pp. 950 - 954, 2014.
[27] H. Zhu and J. Wang, “Chunk-based resource allocation for OFDMA systems,
Part I : chunk allocation,” IEEE Trans. on Commun., vol. 57, no. 9, pp.
2734-2744, Sep. 2009.
[28] H. Zhu and J. Wang, “Chunk-based resource allocation in OFDMA systems-
Part II : joint chunk, power and bit allocation, ” IEEE Trans. on Commun.,
vol. 60, pp. 499-509, no. 2, Feb. 2012.