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In Table 5.4, the initial subchannel pool is f1; : : : ;Ng. N clusters are ordered from
small to large in size in terms of the number of nodes contained in the cluster (break ties
arbitrarily). Smaller clusters are examined rst, because the choice of subchannels makes
more impact to smaller clusters. For each particular cluster, the subchannel for which
the sum capacity is maximum for this cluster is assigned to this cluster (Steps 1 & 2).
The procedure continues on the next cluster with the subchannel pool of one less entry,
i.e., the subchannel that has already been assigned is removed from the pool (Step 3).
The iteration repeats until all clusters are assigned with one subchannel (Step 4). This
heuristic method that iteratively assigns subchannels to clusters is of complexity O(N2).
An alternative method, called random channel assignment, can also be used here to
solve the second-phase problem. In this method, one assignment out of N! choices is
randomly picked as the solution. The complexity of this random assignment method is
O(1). However, the performance of the random channel assignment may not be as good
as that of the heuristic method described above, as it does not take channel condition
into consideration when performing the channel assignment.
5.6 Simulation Results
In this section, we study the performance of the proposed schemes by computer simula-
tion. The simulation setup follows closely the IEEE 802.16m evaluation methodology [6]
and is summarized in Table 5.5.
The ve schemes to be investigated and compared are shown in Table 5.6. ICI-blind
is the traditional OFDMA scheme where no ICI-aware mechanism is employed; i.e., each
130
Object Description
| Title | Resource allocation in OFDM/OFDMA cellular networks: protocol design and performance analysis |
| Author | Chang, Yu-Jung |
| Author email | yujungc@usc.edu; yjrchang@gmail.com |
| Degree | Doctor of Philosophy |
| Document type | Dissertation |
| Degree program | Electrical Engineering |
| School | Viterbi School of Engineering |
| Date defended/completed | 2008-09-09 |
| Date submitted | 2008 |
| Restricted until | Unrestricted |
| Date published | 2008-10-29 |
| Advisor (committee chair) | Kuo, C.-C. Jay |
| Advisor (committee member) |
Neely, Michael J. Govindan, Ramesh |
| Abstract | Orthogonal frequency division multiplexing (OFDM) and orthogonal frequency division multiple access (OFDMA) are two promising technologies adopted in the IEEE 802.16 standard to support broadband wireless access as well as multimedia quality-of-service (QoS). In this dissertation, we discuss several important topics regarding OFDM/OFDMA: cross-layer performance analysis of OFDM and OFDMA downlinks in terms of several QoS metrics; the medium access control (MAC) protocol design for the OFDMA uplink; and the inter-cell interference (ICI) management in multi-cell OFDMA networks through a systematic approach.; First, performance analysis of OFDM-TDMA and OFDMA networks is performed in terms of cross-layer QoS measures which include the bit rate and the bit error rate (BER) in the physical layer, and packet average throughput/delay and packet maximum delay in the link layer. We adopt a cross-layer QoS framework similar to that in IEEE 802.16, where service classification, flow control and opportunistic scheduling with different subcarrier/bit allocation schemes are implemented. Our analysis provides important insights into the performance differences of these two multiaccess systems. In addition, it is shown by analysis and simulation that OFDMA outperforms OFDM-TDMA in QoS metrics of interest. Thus, we conclude that OFDMA has higher potential in supporting multimedia services.; Second, a distributed MAC algorithm for uplink OFDMA networks under the IEEE 802.16 framework is proposed and analyzed. We present a simple yet efficient algorithm to enhance the system throughput by integrating opportunistic medium access and collision resolution through random subchannel backoff. Consequently, the resulting algorithm is called the opportunistic access with random subchannel backoff (OARSB) scheme. OARSB not only achieves distributed coordination among users but also reduces the amount of information exchange between the base station and users. The throughput and delay performance analysis of OARSB is conducted, and the superior performance of OARSB over an existing scheme is demonstrated by analysis as well as computer simulation. Besides, the proposed OARSB scheme can be easily implemented in 802.16 due to its simplicity.; Lastly, a practical and low-complexity multi-cell OFDMA downlink channel assignment method using a graphic framework is proposed. Our solution consists of two phases: 1) a coarse-scale inter-cell interference (ICI) management scheme and 2) a fine-scale channel-aware resource allocation scheme. In the first phase, the task of managing the performance-limiting ICI in cellular networks is accomplished by a graphic approach, in which no ICI measurement is needed and state-of-the-art ICI management schemes such as ICI coordination (ICIC) and base station cooperation (BSC) can be incorporated easily. In the second phase, channel assignment is accomplished by taking instantaneous channel conditions into account. Heuristic algorithms are proposed to solve both phases of the problem efficiently. Extensive simulation is conducted for various practical scenarios to demonstrate the superior performance of the proposed solution against the conventional OFDMA allocation scheme. Thanks to its practicality and low complexity, the proposed scheme can be used in next generation cellular systems such as the 3GPP Long Term Evolution (LTE) and IEEE 802.16m. |
| Keyword | OFDM; OFDMA; MAC protocol design; performance analysis; resource allocation; interference management; IEEE 802.16; cellular networks |
| Language | English |
| Part of collection | University of Southern California dissertations and theses |
| Publisher (of the original version) | University of Southern California |
| Place of publication (of the original version) | Los Angeles, California |
| Publisher (of the digital version) | University of Southern California. Libraries |
| Provenance | Electronically uploaded by the author |
| Type | texts |
| Legacy record ID | usctheses-m1704 |
| Contributing entity | University of Southern California |
| Rights | Chang, Yu-Jung |
| Repository name | Libraries, University of Southern California |
| Repository address | Los Angeles, California |
| Repository email | cisadmin@lib.usc.edu |
| Filename | etd-Chang-2392 |
| Archival file | uscthesesreloadpub_Volume40/etd-Chang-2392.pdf |
Description
| Title | Page 144 |
| Contributing entity | University of Southern California |
| Repository email | cisadmin@lib.usc.edu |
| Full text | In Table 5.4, the initial subchannel pool is f1; : : : ;Ng. N clusters are ordered from small to large in size in terms of the number of nodes contained in the cluster (break ties arbitrarily). Smaller clusters are examined rst, because the choice of subchannels makes more impact to smaller clusters. For each particular cluster, the subchannel for which the sum capacity is maximum for this cluster is assigned to this cluster (Steps 1 & 2). The procedure continues on the next cluster with the subchannel pool of one less entry, i.e., the subchannel that has already been assigned is removed from the pool (Step 3). The iteration repeats until all clusters are assigned with one subchannel (Step 4). This heuristic method that iteratively assigns subchannels to clusters is of complexity O(N2). An alternative method, called random channel assignment, can also be used here to solve the second-phase problem. In this method, one assignment out of N! choices is randomly picked as the solution. The complexity of this random assignment method is O(1). However, the performance of the random channel assignment may not be as good as that of the heuristic method described above, as it does not take channel condition into consideration when performing the channel assignment. 5.6 Simulation Results In this section, we study the performance of the proposed schemes by computer simula- tion. The simulation setup follows closely the IEEE 802.16m evaluation methodology [6] and is summarized in Table 5.5. The ve schemes to be investigated and compared are shown in Table 5.6. ICI-blind is the traditional OFDMA scheme where no ICI-aware mechanism is employed; i.e., each 130 |
