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5.3.2 Multi-cell OFDMA Resource Allocation Problem
Here we describe the multi-cell OFDMA channel allocation problem in the reuse-1 net-
work. Let Y = [ymn] be the channel assignment matrix whose entry ymn is equal to one
if subchannel n is assigned to MS m and zero, otherwise. Then, the centralized multi-cell
OFDMA resource allocation problem can be formulated as follows.
P: Find an assignment matrix, denoted by Y(P)
opt , that maximizes the total capacity,
i.e.,
Y(P)
opt = arg max
Y
MX
m=1
XN
n=1
log2(1 + SINRmn) ymn; (5.6)
subject to the following two constraints
8>><
>>:
C1: 8n 2 f1; 2; : : : ;Ng; if ym0n = 1; then ymn = 0; for all m for which Am = Am0 ;
C2: 8m 2 f1; 2; : : : ;Mg;Rm =
PN
n=1 ymn:
(5.7)
Note that constraint C1 guarantees that a subchannel is used by at most one MS
in each cell, i.e., no intra-cell interference. Constraint C2 states that the resource block
demand3 of MS m, namely Rm, is met for all m. Note that constraints C1 and C2 are
to be met simultaneously. Thus, if all served MSs in a particular cell l have an equal
resource block demand of R > 1, the number of served MSs in cell l can be at most N=R,
i.e., Ml N=R.
Any attempt to solve Problem P directly would encounter two challenges. First,
SINRmn is unavailable before actual resource allocation since the interference for MS
3The number of subchannels will be equal to the throughput if all subchannels are statistically equal.
Although the SINR of each subchannel is likely statistically unequal in the multi-cell scenario, in light
of the complex inter-dependency of SINR and the di culty to obtain exact statistics, we use C2 to
approximate the throughput requirement.
112
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 126 |
| Contributing entity | University of Southern California |
| Repository email | cisadmin@lib.usc.edu |
| Full text | 5.3.2 Multi-cell OFDMA Resource Allocation Problem Here we describe the multi-cell OFDMA channel allocation problem in the reuse-1 net- work. Let Y = [ymn] be the channel assignment matrix whose entry ymn is equal to one if subchannel n is assigned to MS m and zero, otherwise. Then, the centralized multi-cell OFDMA resource allocation problem can be formulated as follows. P: Find an assignment matrix, denoted by Y(P) opt , that maximizes the total capacity, i.e., Y(P) opt = arg max Y MX m=1 XN n=1 log2(1 + SINRmn) ymn; (5.6) subject to the following two constraints 8>>< >>: C1: 8n 2 f1; 2; : : : ;Ng; if ym0n = 1; then ymn = 0; for all m for which Am = Am0 ; C2: 8m 2 f1; 2; : : : ;Mg;Rm = PN n=1 ymn: (5.7) Note that constraint C1 guarantees that a subchannel is used by at most one MS in each cell, i.e., no intra-cell interference. Constraint C2 states that the resource block demand3 of MS m, namely Rm, is met for all m. Note that constraints C1 and C2 are to be met simultaneously. Thus, if all served MSs in a particular cell l have an equal resource block demand of R > 1, the number of served MSs in cell l can be at most N=R, i.e., Ml N=R. Any attempt to solve Problem P directly would encounter two challenges. First, SINRmn is unavailable before actual resource allocation since the interference for MS 3The number of subchannels will be equal to the throughput if all subchannels are statistically equal. Although the SINR of each subchannel is likely statistically unequal in the multi-cell scenario, in light of the complex inter-dependency of SINR and the di culty to obtain exact statistics, we use C2 to approximate the throughput requirement. 112 |
