In this dissertation, the radio resource allocation schemes in wireless network are studied, and the Qos guarantee radio resource management schemes are investigated in both PAN and WMAN.
For IEEE 802.11 WLAN to provide low delay variance, an adaptive p-persistent-based (APP) medium access control (MAC) scheme [46]-[48] is presented in Chapter 2. Permission probabilities of transmission for stations being incurred with different packet delays can be differentiated through the APP MAC scheme and it is designed as a function of the numbers of retransmissions and re-backoffs so that stations with larger packet delay can have higher permission probability. Moreover, the scheme is modeled by a Markov-chain and successfully analyzed, in which the system throughput and delay are derived from. For multimedia services, the APP MAC scheme adaptively gives transmission stations which are in different access category and with various waiting delay differentiated permission probabilities.
For uplinks in IEEE 802.16 wireless communication systems, a dynamic priority resource allocation (DPRA) scheme [33]-[34] is proposed in Chapter 4. The DPRA scheme dynamically gives four types of service traffic based on their urgency degrees
priority values and allocates system radio resources according to their priority values. It can satisfy differentiated QoS requirements and maximize the system throughput. Also, in order for packets of users to conform the uplink frame structure of IEEE 802.16 to fulfill QoS requirement and reduce the computational complexity, the DPRA scheme performs consistent allocation.
For downlink multiuser MIMO-OFDMA systems, a utility-based throughput maximization and complexity reduction (U_TMCR) scheduling scheme [43]-[44] is proposed in Chapter 3. The U_TMCR scheme allocates subchannels, antenna sequence, and modulation order to multimedia users with goals not only to reduce computational complexity but also to maximize system throughput under QoS guarantee. Based on each user’s channel quality and QoS requirements, both a utility function for every user is designed and the scheduling is formulated into an optimization problem of overall system utility function subject to system constraints by the U_TMCR scheme. It also contains a heuristic TMCR algorithm for efficiently solving the optimization problem.
Finally, the conclusive statements and future research topics are addressed in Chapter 5.
Chapter 2
Analysis of an Adaptive P-Persistent MAC Scheme for WLAN Providing Delay Fairness
2.1 Introduction
In the IEEE 802.11, the fundamental mechanism to access the medium is called distributed coordination function (DCF), which is based on carrier sense multiple access with collision avoidance (CSMA/CA) protocol. Retransmissions of collided packets are managed by binary exponential backoff (BEB) rules. The IEEE standard also defines an optional point coordination function (PCF), which is a centralized MAC protocol to support collision free and time bounded services. Both the DCF and PCF can operate concurrently with the same basic service set (BSS) to alternate contention and contention-free periods.
In the DCF mode, if a station has a new packet to transmit, it will sense the channel
state firstly. The station transmits only if the channel is idle for a period of time equal to a DCF inter frame space (DIFS). Otherwise, the station persists to monitor the channel until the measured idle period equals a DIFS. Additionally, the DCF also adopts a BEB scheme to avoid the occurrence of packet collision.
Traditional MAC scheme accompanying with the BEB algorithm is one of the most widely used scheme for data transmission, because of its simplicity and high channel utilization. However, the fairness of the BEB algorithm is very poor in some cases. For example: considering a WLAN with n stations using the DCF mode to access channel, and the stations always have packets to transmit. When one station transmits successfully, it will decrease the size of the contention window to the size of the initial contention window (W0). Before it transmits a next packet, it has to uniformly choose a backoff counter in the backoff interval, (0, W0-1). At that instance, other stations which had experienced collided transmission have a larger backoff interval. As a result, a station with new packet in queue has higher probability to access channel than other waiting stations; that is, unfairness occurs.
Some algorithms to solve the fairness problem of MAC in WLAN were proposed [14], [15]. A multiplicative increase linear decrease (MILD) scheme was proposed in MACAW protocol for WLAN [14]. In the MILD scheme, the contention window of a collided station was increased by multiplying an amount of 1.5, while the contention window of a successful station is decreased by one step. Here, the step was defined as the transmission time of a packet. In the MACAW protocol, the current backoff interval information was included in each transmitted packet, and also a backoff interval copy mechanism implemented in each station copied the backoff intervals of the overheard successful transmitters.
it incurs a new problem. Consider the same example as above. When a station successfully transmits a packet with large contention window, other stations waiting to transmit packets change their backoff interval to the large contention window because of the backoff interval copy mechanism applied in MILD scheme. This algorithm works well when many stations happen to transmit at the same time because the probability of collision decreases. But, it results in long channel idle time and decreases channel utilization if only few stations contend for the wireless channel.
Haas and Deng proposed a new MAC scheme [45] named sensing backoff algorithm (SBA). The SBA is an optimized version of MILD algorithm in slotted ALOHA networks. In the SBA, upon collision, stations multiplied theirs contention windows by α (α>1). The backoff intervals of the transmitting station and the receiving station, after each successful transmission, were multiplied by θ (θ<1). The contention windows of all active stations sensing a successful transmission were decreased by β steps. Once the value of α was chosen, the optimization parameters for SBA can be accordingly determined. The SBA guarantees that the successful transmission probabilities of other stations are the same as that of the previously successful station; that is, the stations have the same transmission probability regardless of the number of retransmission. Unfortunately, SBA does not resolve the problem of large delay variance among stations.
Yamada, Morikawa, and Aoyama proposed a decentralized delay fluctuation control (DDFC) MAC mechanism [15], where the contention window is changed according the packet waiting time. The larger the packet waiting time is, the smaller the contention window will be. The DDFC in nature lessens variance of waiting time from enqueueing to successful transmission. Unfortunately, the channel utilization in DDFC is still low due to the small contention windows and high collision probabilities.
To support multimedia services for the IEEE 802.11e WLAN, dynamic contention window (CW) schemes [16]-[18], different maximum packet length scheme [18], and various interframe space (IFS) schemes [18]-[20] are usually adopted to design the priority differentiation. However, these solutions would still cause large delay variance in the same access category (AC) because of the backoff scheme. Noticeably, higher delay variance results in larger probability of quality-of-service (QoS) violation of multimedia traffic due to excess delay.
This chapter proposes and analyzes an adaptive p-persistent-based (APP) MAC scheme for the IEEE 802.11 WLAN proposed in [46], [47]. The APP MAC scheme, installed in a station, dynamically adjusts the permission probability of transmission for the station itself, and sets the permission probability as a function of the numbers of retransmissions and re-backoffs. The station with longer packet delay, implying larger numbers of retransmissions and re-backoffs, is given higher permission probability.
Therefore, the packet delay variance of station for each access can be decreased and the WLAN can provide good delay fairness for stations in each access. The Markov-chain model [20], [49]-[51], is adopted to analyze the proposed APP MAC scheme. The performance measures such as collision probability, system throughput, and mean delay are successfully obtained. Numerical and simulation results show that the APP MAC scheme can effectively reduce the delay variance and thus achieve the delay fairness.
The collision probability is decreased and the system throughput is enhanced, compared to conventional schemes. Moreover, discrepancy between numerical and simulation results is provided to corroborate the analyses. These results reveal that the analyses are quite accurate.
For multimedia services, the various initial contention window (CWmin) and DCF
initial permission probabilities to various ACs to further differentiate their priorities.
Moreover, it adaptively adjusts the permission probability of stations in each AC according to their respective waiting delays to reduce the delay variance of stations within the same AC.
The rest of the chapter 2 is organized as follows. Section 2.2 describes the system model, and section 2.3 introduces the APP MAC scheme. The mathematical analysis of the APP MAC scheme is given in section 2.4. Section 2.5 illustrates the performance comparisons of the APP MAC scheme and other conventional methods, such as BEB MAC and DDFC MAC, by numerical and simulation results. Finally, concluding remarks are given in section 2.6.