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overlapping channel resources to neighboring cell-edge regions (i.e., A1, A4 and A5; B1,
B2 and B3; C1, C6 and C7) to allow cooperation.
5.3 System Model and Problem Description
5.3.1 System Model and SINR Derivation
We consider a downlink hexagonal cellular network as described in Sec. 5.2.1 with L base
stations (BSs), each with NT antennas, and Ml MSs, each with NR antennas, served by
the l-th BS. The total number of MSs in the entire network is therefore M =
PL
l=1Ml.
Each MS is labeled as either a cell-center or a cell-edge user, depending on its proximity
to the BS. Assume a set of N subchannels is available for resource allocation, and the
frequency reuse factor is one, i.e., each BS will use all N subchannels. Note that due
to the intra-cell allocation constraint in OFDMA networks, which restricts the use of a
subchannel by at most one MS within the same cell, the number of served MSs in cell l
must be less than or equal to the number of subchannels, i.e., Ml N for all l's.
Signal transmission in the multi-cell OFDMA system is modeled as follows. We con-
sider an arbitrary symbol in an OFDMA frame for the interference study in the ensuing
discussion. Let the NR NT matrix H(l)
mn represent the channel from BS l to MS m in
the subchannel n, which has complex Gaussian elements. Let the Lmn 1 vector smn
be the transmitted data intended for MS m using subchannel n, which has zero mean
and normalized power, i.e., E[smnsH
mn] = ILmn. The data vector smn is precoded by an
NT Lmn precoding matrix, Tmn, which also has normalized power, i.e., jjTmnjj2
F = 1,
where jj jj2
F is the Frobenius norm of a matrix.
109
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 123 |
| Contributing entity | University of Southern California |
| Repository email | cisadmin@lib.usc.edu |
| Full text | overlapping channel resources to neighboring cell-edge regions (i.e., A1, A4 and A5; B1, B2 and B3; C1, C6 and C7) to allow cooperation. 5.3 System Model and Problem Description 5.3.1 System Model and SINR Derivation We consider a downlink hexagonal cellular network as described in Sec. 5.2.1 with L base stations (BSs), each with NT antennas, and Ml MSs, each with NR antennas, served by the l-th BS. The total number of MSs in the entire network is therefore M = PL l=1Ml. Each MS is labeled as either a cell-center or a cell-edge user, depending on its proximity to the BS. Assume a set of N subchannels is available for resource allocation, and the frequency reuse factor is one, i.e., each BS will use all N subchannels. Note that due to the intra-cell allocation constraint in OFDMA networks, which restricts the use of a subchannel by at most one MS within the same cell, the number of served MSs in cell l must be less than or equal to the number of subchannels, i.e., Ml N for all l's. Signal transmission in the multi-cell OFDMA system is modeled as follows. We con- sider an arbitrary symbol in an OFDMA frame for the interference study in the ensuing discussion. Let the NR NT matrix H(l) mn represent the channel from BS l to MS m in the subchannel n, which has complex Gaussian elements. Let the Lmn 1 vector smn be the transmitted data intended for MS m using subchannel n, which has zero mean and normalized power, i.e., E[smnsH mn] = ILmn. The data vector smn is precoded by an NT Lmn precoding matrix, Tmn, which also has normalized power, i.e., jjTmnjj2 F = 1, where jj jj2 F is the Frobenius norm of a matrix. 109 |
