We allocate all the subcarriers not belonging to the ranging channel to one single DSS who uses QPSK to modulate the data on the subcarriers without forward error control coding. Because the ICI in the first OFDM symbol of the ranging opportunity is not only caused by CFOs but also the RSSs’ large timing offsets, we expected much more severe interference in the first OFDM symbol than that in the second. In Figure 6.10, this fact is reflected by the error floors of the SUD, which are as high as 1% and 3% respectively for the 8-RSS and 12-RSS cases. The proposed SMUD can effectively suppress the interference from as many as 8 RSSs and lower the error floors to 10−5 and 4× 10−4 in CH-A and CH-B respectively. When
there are 12 RSSs many of whom are not detected by the SMUD, our interference cancellation scheme still manages to lower the error floors to a fraction of their original levels in both channels. Compared to the SMUD, the RC-SMUD has only 1dB performance loss in all the cases, which means that it is a quite cost-effective alternative if the complexity of the SMUD is too high for some practical OFDMA systems.
6.7
Summary
The contention based ranging channel is allocated for joint user detection and syn- chronization in the uplink of practical OFDMA communication systems. Because
6.7 Summary 147 10 10.5 11 11.5 12 12.5 13 13.5 14 10−6 10−5 10−4 10−3 10−2 10−1
DSS Signal to Noise Ratio on Each Subcarrier (dB)
DSS 1st Symbol Bit Error Rate in CH−A
SUD, 8 Users SUD, 12 Users SMUD, 8 Users SMUD, 12 Users RC−SMUD, 8 Users RC−SMUD, 12 Users 2nd Symbol, 8 Users 2nd Symbol, 12 Users (a) CH-A. 10 10.5 11 11.5 12 12.5 13 13.5 14 10−5 10−4 10−3 10−2 10−1
DSS Signal to Noise Ratio on Each Subcarrier (dB)
DSS 1st Symbol Bit Error Rate in CH−B
SUD, 8 Users SUD, 12 Users SMUD, 8 Users SMUD, 12 Users RC−SMUD, 8 Users RC−SMUD, 12 Users 2nd Symbol, 8 Users 2nd Symbol, 12 Users (b) CH-B.
multiple users share the same set of time slots and subcarriers for uplink trans- mission, the multiple access interference (MAI) limits the performance of ranging channel.
In this chapter we have proposed a successive ranging channel detector to mit- igate the MAI and improve the user detection performance. In every iteration, the proposed method detects the most likely channel path of active RSSs, then jointly estimates the channels for all the detected paths and removes their interfer- ence before next iteration. Using this approach, near single-user performance was achieved. It was shown that the user-by-user iteration approach of the SAGE based algorithms could not work for the ranging channel due to the insufficient number of subcarriers to distinguish the multipath channels of all possible ranging codes. Moreover, the complexity of the SAGE methods is much higher than that of the SMUD. Compared to the conventional single-user detection methods, the proposed algorithm is able to detect low-power users at much higher success rate. Not only the ranging users, but also the data subscriber stations benefit from the reduced ICI on the data subcarriers. This was realized by removing the interference of the reconstructed ranging signal, and detecting the ranging users before they boost the power. To further improve the efficiency of the proposed successive multiuser detector, we have proposed a reduced complexity version of the original algorithm that can be implemented simply by a number of IFFT functions. Simulation results showed a slight performance degradation resulted from the reduced complexity.
Chapter 7
System Performance of Ranging
Detectors
7.1
Introduction
Ranging is the process of establishing an initial link in the uplink and initiat- ing closed loop timing control such that ISI and ICI can be minimized. In the IEEE 802.16 [4] standard, two ranging methods are specified, initial ranging and periodic ranging. The initial ranging is needed when a SS enters a network or performs a handover. Once the SS receives an acknowledgement from the BS with the allocated connection identification number (CID), the SS enters the network and uses periodic ranging to request bandwidth and keep track of its transmission parameters.
Consider a wireless communication system where a BS serves a number of SSs with a given number of ranging opportunities. In the previous chapter, we have obtained the missed detection probabilities for the ranging channel detectors via simulations, however, it is more interesting from a system point of view to know the maximum number of SSs a BS can serve, or, for a given number of SSs what is the minimum number of ranging opportunities required. This information is useful for the BS to optimize the bandwidth allocation for ranging and avoid under-supplying or over-supplying the ranging opportunities, both of which incur a loss in system data throughput.
In this chapter, we quantify the relationship between the number of ranging opportunities and the maximum number of SSs a BS can serve with a given ranging channel detector whose missed detection probabilities have been obtained from the simulations. For periodic ranging, we assume the SSs are stationary within a cell,
and analyze the maximum number of users that can be served by the BS with a given number of ranging opportunities. For initial ranging, we assume the SSs are entering from neighboring cells and need to perform the handover operations. We analyze the handover success rate and the average time needed by the handover process.
For illustration purpose, three ranging channel detection algorithms are consid- ered in this study: the differential decoding based method (Diff) [131], correlation based method (SUD) [83, 84], and the reduced complexity successive multiuser de- tection method (RC-SMUD) proposed in Chapter 6 of this thesis. The complexity of these ranging channel detectors is summarized in Table 7.1, whereNc is the num-
ber of available ranging codes, Nr is the number of subcarriers allocated to ranging
channel, N is the number of subcarriers, Imax is the pre-defined maximum num-
ber of iterations for the RC-SMUD. Nevertheless, the methods developed in this chapter for system-level performance analysis are also applicable to other ranging channel detectors, e.g., the full complexity SMUD algorithm described in Chapter 6 of this thesis.
Table 7.1: Complexity of the ranging channel detectors.
Diff [131] SUD [83] RC-SMUD
O(NcNr) O(NcN log2N) O(ImaxNcN log2N)