近年來，無線個人通訊已經大大地改進了個體之間的資料傳輸。除了H2H通訊外，在蜂巢式網路中發展M2M通訊也逐漸受到矚目。其中，提供多樣性及好的服務品質(QoS)是M2M通訊中最重要的需求之一。在M2M通訊中，不同的服務品質需求(QoS)需要有合適的資源分配方法。在LTE-A網路的M2M通訊中，為使現有資源依據不同服務品質需求(QoS)而能夠妥善被分配給M2M裝置及H2H使用者，尋找合適的資源分配方法將是個很有挑戰性的議題。為滿足不同服務品質需求(QoS)進而有效地分配資源區塊(resource blocks)，我們提出以下的M2M通訊方法：「將依據不同無線傳輸協定組成群組，在每個群組下再依據不同服務品質需求(QoS)組成小的群組」。並且，我們在單載波分頻多工存取(SC-FDMA)為基底的LTE-A網路中進行聯合的資源區塊和功率分配。我們將此架構表示成總流通量(sum-throughput)最大化問題，其限制條件必須滿足受限於LTE-A上行網路中單載波分頻多工存取(SC-FDMA)為基底的資源區塊與功率分配，並確保M2M裝置的服務品質需求(QoS)。由於使用單載波分頻多工存取(SC-FDMA)做為LTE-A上行網路的空中介面，增加了資源分配問題的複雜度。我們為克服分析和計算上的複雜度，於是我們將原問題轉換為二進制整數規劃問題(BIP)，並用拉格朗茲對偶理論(Lagrange duality theory)求解對偶問題。我們也將提出的演算法與貪婪法比較。我們由模擬的結果可知，在滿足服務品質需求(QoS)下最大化流通量(throughput)，我們提出的演算法表現較貪婪法好，並且為一個更接近窮舉法的設計。除此之外，為了闡述隨機存取中的擁塞問題，我們提出單載波分頻分碼多工存取(SC-FDMA-CDMA)機制，其中每個M2M裝置的前引訊號被分配到一個碼，使eNB可偵測到每個前引訊號，並決定有多少M2M裝置被一個前引訊號選到。在我們所提出的機制中，選擇相同前引訊號的裝置，藉著用相同的碼在相同的通道傳輸他們的資料。因此，大大地降低了隨機存取過程。除此之外，我們所提出的機制可以大大地降低M2M裝置資料傳輸所需求的資源區塊(resource blocks)數，透過合併M2M裝置產生的許多封包成為一個資源區塊(resource blocks)。更近一步地，不同長度的超級正交碼(DLSOC)被進一步提出，使得現行使用的碼產生的之多重存取干擾multiple access interference (MAI)和多路徑干擾multi-path interference (MI)問題，藉由應用超級正交碼的創新技術，在同步和非同步狀態下都會被大大地消除。

Recently, wireless personal communications have been widely proliferated to exchange data
among individuals. In addition to human-to-human (H2H) communications, the introduction
of machine-to-machine (M2M) communications into cellular networks is vigorously being developed. Providing diverse and strict quality of service (QoS) guarantees is one of the most important requirements in M2M communications. Such diverse QoS requirements particularly need for appropriate resource allocation that can be applied to M2M communications.
This issue becomes more challenging with the enabling of M2M communications in LTE-A networks as the available resources have to be shared between M2M devices and H2H users, owning different QoS requirements. To efficiently allocate resource blocks (RBs) for M2M devices while satisfying QoS requirements, we propose the group based M2M communications in which M2M devices are grouped based on their wireless transmission protocols and clustered based on QoS characteristics and requirements. Then, we perform joint RB and power allocation in SC-FDMA-based LTE-A network. We formulate our framework as a sum-throughput maximization problem while respecting all the constraints associated with the SC-FDMA regarding to the RB and power allocation in LTE-A uplink network and considering QoS guarantees for the M2M devices. The specific constraints of SC-FDMA as an uplink air interface in LTE-A networks complicate the resource allocation problem. We overcome the analytical and computational intractability by first transforming the original problem into a binary integer programming (BIP) problem and then formulating its dual problem using the Lagrange duality theory. The proposed algorithm is compared with Greedy algorithm [35] as well. Numerical results show that the proposed algorithm not only outperforms Greedy algorithm in terms of throughput maximization while satisfying QoS requirements, but also performs closer to the optimal design. On the other hand, to address congestion problem in random access (RA), we introduce SC-FDMA-CDMA scheme in which a code is assigned to the preamble sent by M2M devices enabling eNB to detect each preamble and also determine how many M2M devices have selected each preamble. In the proposed scheme, the devices that selected the same preamble, transmit their data at the same data channel by utilizing the code. Hence, the RA process is significantly reduced. In addition, the proposed scheme can significantly reduce the number of RBs required to transmit data of M2M devices through incorporating many packets generated by M2M devices into one RB. Furthermore, different lengths super orthogonal codes (DLSOC) are further proposed so that the issues such as multiple access interference (MAI) and multipath interference (MI) associated with currently used codes could be significantly eliminated for both synchronous and asynchronous cases by utilizing the novel technology of the super orthogonal
Index Terms – M2M communications, LTE-Advanced, Scheduling, grouping, Power allocation, SC-FDMA-CDMA, Resource allocation, QoS, Random access

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