- Research Article
- Open Access

# On Adaptive Contention Resolution Schemes for IEEE 802.16 BWA Systems

- Chih-Heng Ke
^{1}and - Der-Jiunn Deng
^{2}Email author

**2009**:205057

https://doi.org/10.1155/2009/205057

© C.-H. Ke and D.-J. Deng. 2009

**Received:**28 January 2009**Accepted:**17 May 2009**Published:**28 June 2009

## Abstract

According to the latest version of the IEEE 802.16 standard, the mandatory contention resolution method is the truncated binary exponential backoff, with the initial window size and the maximum window size controlled by the base station. However, the problem of choosing the right set of backoff parameters for the current network level remains unsolved and left as an open issue since this strategy might incur a high collision probability and the channel utilization could be degraded in congested scenario. In this paper, we propose two pragmatic adaptive algorithms, namely semi-dynamic and quasi-dynamic contention resolution schemes, that allow the base station to adjust its backoff window size based on current channel status. By controlling the size of backoff window according to varying network conditions, both schemes are able to achieve higher performance in comparison with the legacy IEEE 802.16 standard.

## Keywords

- Contention Window
- Fairness Index
- Bandwidth Request
- Contention Period
- Contention Window Size

## 1. Introduction

High-speed transmission, fast deployment, and cost saving have made *Broadband Wireless Access* (BWA) systems a rapidly emerging field of activity in computer networking, attracting significant interests in the communities of academia and industry. In the mean time, the IEEE standard for BWA systems, IEEE 802.16 [1–3], has gained global acceptance and popularity in wireless computer networking markets and is also anticipated to take place of broadband access solutions like *digital subscriber line* (DSL) and cable.

*point-to-multipoint*(PMP) and

*mesh*(optional) modes. In the PMP mode, the nodes are organized into a cellular-like structure, where a

*base station*(BS) serves a set of

*subscriber stations*(SSs) within the same antenna sector in a broadcast manner, as shown in Figure 1.

The communication path between SSs and BS has two directions: uplink channel (from SSs to BS) and downlink channel (from BS to SSs). The downlink channel is a broadcast channel, while the bandwidth of uplink channel is shared by the SSs. The subframe in uplink channel includes three periods: Initial Maintenance period, Request Connection Opportunities period, and Scheduled Data grants period. The BS announces these periods and associates burst classes in the preceding downlink subframe's *uplink map* (UL-MAP).

Initial ranging and bandwidth request are two primary parts of the Call Admission Control (CAC) procedure. The BS periodically reserves bandwidth in the uplink channel for SSs to register or send their bandwidth request. When a SS needs registration or bandwidth, it has to go through the contention resolution procedure to send its requests.

The IEEE 802.16 contention resolution mechanism is controlled by two sets of parameters: the number of the contention slots and the backoff initial/maximum window values. These parameters are set at the BS and transmitted to SSs in the UL-MAP. When an SS has information to send and wants to enter the contention resolution process, it sets its internal backoff window size equal to the request size of initial backoff window defined in the *uplink channel descriptor* (UCD) message. The SS randomly selects a number within its initial backoff window. This random value indicates the number of contention transmission opportunities that the SS defers before transmitting. However, collisions might still occur if two or more SSs select the same backoff value. When this happens, the SS increases its backoff window by a factor of two, as long as it is less than the maximum backoff window. The SS randomly selects a number within its new backoff window and repeats the deferring process described above. This retry process continues until the maximum number of retries has been reached.

According to the IEEE 802.16 standard, the backoff parameters of its collision resolution mechanism are far from optimal setting since it selects a small initial value of backoff window by a naive assumption of a low level of congestion in the system. Hence, the problem of choosing the right set of backoff parameters for the current network level remains unsolved and left as an open issue since this strategy might incur a high collision probability and the channel utilization could be degraded in congested scenario.

Although in literatures there have been excellent discussions on the issues on contention resolution mechanism and its performance analysis [4, 5]. However, these studies do not propose any mechanisms to force the SSs to adopt an adaptive backoff window size that maximizes the channel capacity for current channel status. In [6], Yao et al. analyzed the impact of contention slots allocation on system throughput and thus proposed an algorithm to optimize the utilization of uplink bandwidth by dynamically adjust the number of contention slots. In [7], Sayenko et al. presented analytical calculations to determine optimal values for the backoff initial/maximum values and an optimal number of the request transmission opportunities. In [8], Lin et al. proposed an efficient performance improvement method by using dynamic window adjustment for initial ranging. However, none of the above studies is satisfactory since they did not tell us how to run-time estimate the channel status. The algorithm proposed in [9] automatically adjusts the initial contention window to a near optimal point according to the traffic activity, thus avoiding bandwidth wastage due to improper contention window setting. However, this scheme was designed for WLANs, and we did not know whether the proposed algorithm can be applied to IEEE 802.16 standard.

Based on above observations, we propose that a proper choice of the size of backoff window in accordance with current channel status, which has a great influence on overall network performance. Hence, in this paper, two pragmatic adaptive algorithms, namely semi-dynamic and quasi-dynamic contention resolution scheme, that allow the base station to adjust its backoff window size dynamically are proposed. Both schemes can be implemented in the present IEEE 802.16 standard with only relatively minor modifications and use very simple feedback signals. In addition to the analytical analysis, we have also carried out comprehensive simulations implemented by network simulator NS2 [10] to evaluate the performance of the proposed schemes. The results show that both schemes are able to achieve higher performance in comparison with the legacy IEEE 802.16 standard.

The remainder of this paper is organized as follows. Sections 2 and 3 introduce the proposed semi-dynamic and quasi-dynamic contention resolution schemes, respectively. Simulation and experimental results are given in Section 4, followed by Section 5 which concludes this paper.

## 2. Semi-Dynamic Contention Resolution Scheme

Notations and variables used in analytical analysis.

Notations and variables | Meaning and explanation |
---|---|

Number of estimated active connections | |

Probability of a contention failure | |

Transmission probability | |

Utilization factor of contention period | |

Optimal value of parameter | |

Initial backoff window size | |

Maximum backoff window size | |

Maximum number of backoff stages | |

Average contention window size | |

Optimal contention window size |

In an IEEE 802.16 BWA system, a low transmission collision rate implies that the number of competing SSs is low, and the contention window should be set small. On the other hand, consecutive transmission collisions indicate that there are numerous competing SSs in the system. In such cases, the size of backoff window should be set considerably large to avoid collisions in the future transmission.

In the proposed semi-dynamic contention resolution scheme, an active SS uses the analytical model described in [11] to estimate the number of competitive SSs, and then a threshold of backoff window size is set to determine the number of competitive SSs. For more details, the reader is referred to our previous work [11].

In the beginning, corresponding to the period of connection start-up, the backoff window is exponentially increased so as to quickly adjust itself to the current channel status. After the backoff window size reaches the threshold, the size of backoff window linearly grows until a packet transmitted successfully. Algorithm 1 describes the proposed scheme.

**Algorithm 1**

**Function** Semi-Dynamic Backoff

**repeat**

**if** Response received from BS **then**

**if** backoff window size
threshold **then**

**if** backoff window size ==
**then**

**else**

backoff window size = backoff window size 2

**else**

backoff window size = backoff window size

**else**

**if** backoff window size
threshold **then**

backoff window size = backoff window size 2

**else**

**if** backoff window size ==
**then**

**else**

backoff window size = backoff window size +

**until** no more packet to transmit

**end**.

*K*, we increase/decrease the size of backoff window exponentially in response to a light network load. On the other hand, we increase/decrease the size of contention window linearly in response to a heavy network load when the contention window size is larger than the threshold.

## 3. Quasi-Dynamic Contention Resolution Scheme

As for the utilization factor of contention period, , it can be obtained by counting the total number of contention attempts observed in the contention period, divided by the total number of observed contention opportunities on which the measurement is taken in the contention period.

Assume that there are *K* connections working in asymptotic conditions in the system, meaning that the transmission queue of each connection is assumed to be always nonempty. Instead of the legacy binary exponential backoff algorithm used in the 802.16 standard, the backoff interval of the proposed analytical model is sampled from a geometric distribution with the parameter *p* and defers the transmission with probability
, and then repeats the procedure at the next empty slot. Based on geometric densities, the probability that there are
failures of Bernoulli trials before the first success is

Hence, the average contention window size is determined by the expected value of random variable *X*, and thus we have

Now let us try to estimate the average backoff window size at a saturation condition. Since the backoff time is uniformly distributed over for the first attempt, the average backoff window size is

Substituting expressed in (2) into (3), we obtain:

Since the probability of a contention failure is defined as the probability that a transmitted request encounters a collision, this yields

From (5), we obtain

Substituting as expressed in (4) into (6), we obtain

Since indicated that a slot in the contention period remains empty, we have

Substituting
and *K* as expressed in (2) and (7), respectively, we can obtain the approximated optimal contention window size
which is defined as follows

## 4. Simulations and Performance Evaluation

### 4.1. Simulation Environment

Default attribute values used in the simulation.

Parameter | Value |
---|---|

MAC layer | |

Channel capacity | 32 Mbps(QPSK) |

Number of subchannels | 30 |

Symbol rate | 16 Megabaud |

Slot size | 1 byte |

Frame duration | 4 ms |

Physical slots per frame | 4000 |

Downlink/uplink ratio | |

Ranging opps. Per frame | 12 OFDMA symbols |

Number of ranging retry | 16 |

Bandwidth request opp. per frame | 12 OFDMA symbols |

Number of bandwidth request retry | 6 |

Backoff start value | 4 |

Backoff end value | 10 |

Initial ranging CID | 0 |

Basic CIDs | 1–1000 |

Primary CIDs | 1001–2000 |

Threshold | 512 |

System time | |

OFDMA symbol time | |

OFDMA frame length | 5 ms |

Ranging interval interval | |

Bandwidth request interval | |

TTG | |

RTG | |

T1-T26 | As defined in IEEE 802.16 standard |

Physical layer | |

Spectrum | 5.0 GHz |

Bandwidth | 5 MHz |

Simulation topology | |

Offered traffic load | 0.12 Mbps |

QPSK 1/2 | 4.99 Mbps |

QPSK 3/4 | 7.48 Mbps |

16-QAM 1/2 | 9.97 Mbps |

16-QAM 3/4 | 14.96 Mbps |

64-QAM 2/3 | 19.95 Mbps |

64-QAM 3/4 | 22.44 Mbps |

QPSK 1/2 | −79 dBm |

QPSK 3/4 | −76 dBm |

16-QAM 1/2 | −72 dBm |

16-QAM 3/4 | −69 dBm |

64-QAM 2/3 | −65 dBm |

64-QAM 3/4 | −63 dBm |

### 4.2. Simulation Results

Finally, we investigate and analyze the performance discrimination of the proposed schemes. We use the fairness index defined by Jain et al. [12] to evaluate how fair it is. The fairness index is defined as

where *n* is the number of connections, and
is the throughput of connection *i*. From Cauchy-Schwartz inequality, we obtain Fairness Index
1, and the equality holds if and only if all
are equal.

Fairness index versus number of connections.

Number of connections | Legacy IEEE 802.16 | Semi-dynamic scheme | Quasi-dynamic scheme | |
---|---|---|---|---|

10 | 0.975299 | 0.979776 | 0.996461 | 0.998155 |

15 | 0.954031 | 0.960398 | 0.993762 | 0.994366 |

20 | 0.933515 | 0.948921 | 0.990311 | 0.992507 |

25 | 0.927668 | 0.945344 | 0.988443 | 0.995792 |

30 | 0.910177 | 0.930308 | 0.973221 | 0.996529 |

35 | 0.889325 | 0.914136 | 0.958744 | 0.988715 |

40 | 0.861827 | 0.892372 | 0.932492 | 0.980814 |

45 | 0.815158 | 0.858453 | 0.887228 | 0.964915 |

50 | 0.738294 | 0.785694 | 0.831944 | 0.948761 |

## 5. Conclusions

Different from the legacy exponential binary backoff algorithm used in the IEEE 802.16 standard, in this paper, we propose two pragmatic adaptive algorithms, namely, semi-dynamic and quasi-dynamic contention resolution scheme, that allow the base station to adjust its backoff window size based on current channel status. Through extensive simulations, we have demonstrated quantitatively the effectiveness of both proposed schemes. Furthermore, the given results show that the quasi-dynamic scheme can achieve better performance than the semi-dynamic scheme in most cases. However, in order to acquire sufficient knowledge of the current channel status, the quasi-dynamic scheme tends to be more computationally complex compared to the semi-dynamic scheme.

## Authors’ Affiliations

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## Copyright

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.