Performance analysis of dynamic channel allocation based on the greedy approach for orthogonal frequency‐division multiple access downlink systems

Cognitive radio has been considered to be one of the main technologies to solve the problem of low spectrum utilization, while the adaptive allocation of network resource is one of the key technologies. A discrete polynary coding immune clonal selection (DPICS)-based joint subcarrier and power allocation algorithm is proposed to solve the resource allocation problem in uplink cognitive OFDM networks. The novelties of DPICS include the following: A unique coding method is adopted to deal with multi-value discrete variables. Compared with the traditional methods, the proposed method can acquire the shortest code. Meanwhile, the constraints of the subcarrier allocation are avoided. A heuristic mutation scheme is used to direct the mutation. Subcarriers are reallocated randomly to the secondary users with larger homotactic noise, which has a large probability to produce the optimal solution and improves the searching process. Subcarriers and power are allocated simultaneously, which is different with the traditional biphasic resource allocation algorithms. The biphasic resource allocation algorithms cannot acquire the subcarrier allocation result and power allocation result simultaneously, which makes the final result imprecise. The proposed algorithm avoids this situation and improves the accuracy of the final result. Compared with state-of-the-art algorithms, the proposed algorithm is shown as effective by simulation results. Copyright

Section: System Modelmentioning

confidence: 99%

Section: Algorithm 1: Mutation Operationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Discrete polynary coding immune clonal selection‐based joint subcarrier and power allocation in uplink cognitive OFDM network

Shang

Zhang

Jiao

et al. 2014

“…Research on wireless data broadcast has been concentrated on indexing, data scheduling, and data retrieval, which can be used to improve the performance of data propagation in wireless networks. Respectively to them, existing approaches are to concisely design index structure for quickly locating the data items among the channels, to suitably place the data items among the channels for determining the broadcast sequence of data items [4,5], and to efficiently find an access pattern among the channels for downloading the requested data items. The work [6,7] discussed in depth on indexing techniques, in which the client first finds the index information of data items among the channels and then locates the data items among the channels.…”

Section: Related Workmentioning

confidence: 99%

Efficient data retrieval algorithms for multiple requests in MIMO wireless networks

Shen

Guo

et al. 2014

SUMMARYGiven a set of multiple channels, a set of multiple requests, where each request contains multiple requested data items and a client equipped with multiple antennae, the multi-antenna-based multirequest data retrieval problem (DRMR-MA) is to find a data retrieval sequence for downloading all data items of the requests allocated to each antenna, such that the maximum access latency of all antennae is minimized. Most existing approaches for the data retrieval problem focus on either single antenna or single request and are hence not directly applicable to DRMR-MA for retrieving multiple requests. This paper proposes two data retrieval algorithms that adopt two different grouping schemes to solve DRMR-MA so that the requests can be suitably allocated to each antenna. To find the data retrieval sequence of each request efficiently, we present a data retrieval scheme that converts a wireless data broadcast system to a special tree. Experimental results show that the proposed scheme is more efficient than other existing schemes.

“…In , the theoretically achievable average channel capacity (in the Shannon sense) per user of a hybrid cellular direct sequence/fast frequency hopping code‐division multiple‐access system, operating in a Rayleigh fading environment, was examined. The paper of Oh and Woo presents a performance analysis of dynamic channel allocation on the basis of the greedy approach for orthogonal frequency‐division multiple‐access downlink systems over Rayleigh fading channels. Relevant work also includes that of Tan et al .…”

Section: Introductionmentioning

confidence: 99%

An optimal solution to resource allocation among soft QoS traffic in wireless network

Tan

Zhu

Zhang

et al. 2013

SUMMARYOptimization theory and nonlinear programming method have successfully been applied into wire-lined networks (e.g., the Internet) in developing efficient resource allocation and congestion control schemes. The resource (e.g., bandwidth) allocation in a communication network has been modeled into an optimization problem: the objective is to maximize the source aggregate utility subject to the network resource constraint. However, for wireless networks, how to allocate the resource among the soft quality of service (QoS) traffic remains an important design challenge. Mathematically, the most difficult comes from the non-concave utility function of soft QoS traffic in the network utility maximization (NUM) problem. Previous result on this problem has only been able to find its sub-optimal solution. Facing this challenge, this paper establishes some key theorems to find the optimal solution and then present a complete algorithm called utility-based allocation for soft QoS to obtain the desired optimal solution. The proposed theorems and algorithm act as designing guidelines for resource allocation of soft QoS traffic in a wireless network, which take into account the total available resource of network, the users' traffic characteristics, and the users' channel qualities. By numerical examples, we illustrate the explicit solution procedures.