On Adaptive Contention Resolution Schemes for IEEE 802.16 BWA Systems

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.

The IEEE 802.16 standard specifies two modes for sharing the wireless medium: 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.

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

backoff window size =

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

backoff window size =

else

backoff window size = backoff window size +

until no more packet to transmit

end.

Figure 2 shows the state transition diagram of backoff window variation in the proposed semi-dynamic contention resolution scheme. In sum, when the current backoff window size is smaller than the threshold, 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.

In order to exploit the information about the actual channel status, we define the probability of contention failure, , to be the probability that a request slot transmitted by the SS of interest fails (collisions), and the utilization factor of contention period, , to be the average utilization rate of contention periods. Recall that the channel status of contention period (initial ranging or bandwidth request) can be generally divided as two states: busy and idle states as shown in Figure 3. It is noted that busy state includes collision and successful contention. Since the absence of an immediate response in the following UL-MAP will be regarded as a failed contention, can be obtained by counting the total number of responses observed in the following UL-MAP, divided by the total number of observed contention attempts on which the measurement is taken in the contention period.

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

(1)

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

(2)

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

(3)

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

(4)

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

(5)

From (5), we obtain

(6)

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

(7)

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

(8)

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

(9)

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.