A distributed message in message aware concurrent transmission protocol in IEEE 802.11 WLANs
© Kang et al.; licensee Springer. 2012
Received: 25 May 2012
Accepted: 20 September 2012
Published: 30 October 2012
The IEEE 802.11 distributed coordination function (DCF) employs the carrier sense technology to avoid frame collisions. However, recent measurement studies demonstrate that the physical layer (PHY) capture effect frequently occurs; even when frames collide, one of them can be decoded successfully if its relative signal strength is high enough. Furthermore, a new wireless PHY technology, called Message In Message (MIM), adopts an advanced preamble detection function to enhance the PHY capture effect. To fully exploit MIM in multi-collision environments, frame transmission orders have to be carefully scheduled. It also requires tight time synchronization at multiple access points (APs), thus induces large overheads. In this article, we propose an opportunistic concurrent transmission protocol called D istributed O pportunistic M IM-aware C oncurrent T ransmission (DOMCT) which exploits the MIM functionality in a distributed manner obliterating the centralized control. In DOMCT, APs first prepare interference MAPs to discover the possible simultaneous MIM transmission opportunities. Detecting the inadvertent frame transmission from a neighboring AP, an AP transmits another frame intentionally if both frames can successfully be decoded at destination nodes by the MIM capture effect. Through both analysis and extensive ns-2 simulations, we show that DOMCT outperforms the legacy DCF by up to 61% and observe comparable performance to that of the centralized approach.
To support the ever growing demands for mobile communications, IEEE 802.11 wireless LANs (WLAN) have continuously evolved to higher speed variants[1, 2]. Despite the improvements in physical layer (PHY) technologies, the goodput of WLANs does not increase in linear proportion to the PHY speed. One limiting factor is large MAC overheads such as back-off time, long protocol header, ACK, and various inter-frame shifts. Many clever schemes that reduce the MAC overheads have been proposed including frame aggregation and binary back-off optimization[4, 5]. These schemes are called as the temporal approach because they reduce the time required for MAC layer operations.
This article deals with the interference, another factor that degrades the WLANs performance. Interference is considered as one of the most important factors that decides wireless network throughput per unit area. Interference avoidance or reduction in multi-hop wireless networks has been the subject of active research during last several years and a plethora of mechanisms[6–8] that mitigate the effect of interference have been introduced. These mechanisms are referred to as a spatial approach because they essentially try to increase the number of simultaneous transmissions per unit area.
Advanced signal processing makes it possible to decode one of simultaneously received frames—i.e., collided frames—successfully if certain conditions are satisfied. The conventional wisdom is that if two or more frames arrive at a receiver at the same time then all of them fail and result in a collision. Recent observations confirm the PHY capture effect[9–11]; if two frames collide within a preamble period, a receiver can successfully lock on to a stronger signal if it is sufficiently more powerful than the other signal. The PHY capture effect improves the system goodput in a single collision domain. However, its performance gain in a multi-hop network is limited because collisions due to hidden terminals can occur randomly and the probability of preamble collisions is not great.
MIM may not be very useful in a single collision domain because the carrier sense function prevents the frame transmission during busy periods. However, in multiple collision domains, MIM enables successful deliveries of otherwise interfering signals. Santhapuri et al.[12, 15] proposed an MIM-aware centralized packet scheduling algorithm called Shuffle that supports concurrent transmissions from multiple APs. Suppose there are two signals interfering with each other. The basic rule of Shuffle is to transmit a relatively weaker signal before a relatively stronger signal so that both signals are successfully decoded via the MIM capture. Shuffle employs a centralized controller that coordinates frame transmission orders of all the APs in consideration. Shuffle, the first approach that deliberately exploits the MIM capability, suffers from the usual drawbacks inherent to the centralized approaches. In addition, it can only be applied to a single autonomous system and also requires tight time synchronization among the APs.
In this article, we propose a Distributed Opportunistic MIM-aware Concurrent Transmission (DOMCT) protocol. In DOMCT, backlogged APs continuously overhear the transmission of neighboring AP, looking for the opportunities of concurrent transmission via MIM. Observing such opportunities, APs autonomously trigger impromptu concurrent transmissions. In a basic mode, APs initiate frame transmission in a random order. DOMCT achieves additional performance gains by employing enhanced mechanisms such as a per-station queue strategy and transmission ranking (TR). By using the per-station queue strategy, DOMCT effectively fetches the MIM capable frames in real time. On the other hand, TR boosts the throughput performance by increasing the opportunities of concurrent transmissions.
Our main contributions are summarized as follows:
We propose a DOMCT protocol. Since DOMCT operates in a distributed manner, it eliminates the tight time synchronization requirement and high control overhead of the centralized scheme. Furthermore, the distributed nature of DOMCT supports backward compatibility with the legacy IEEE 802.11 Distributed Coordination Function (DCF).
We analyze the probability of the MIM capture in a two APs scenario to verify the potential gain from the MIM-aware concurrent transmissions. The result shows that MIM capture can significantly improve the channel utilization.
We devise a per-station queue strategy and TR so that DOMCT achieves additional performance gains by employing those enhanced mechanisms.
We compare the system throughput of DOMCT, DCF, and Shuffle. Our ns-2 simulation shows that DOMCT improves the system throughput by 61% on average compared to the legacy DCF. Furthermore, DOMCT achieves the performance comparable to Shuffle, the state-of-the-art centralized approach.
The rest of the article is organized as follows. We present the related work in the next section. The detailed description of DOMCT protocol including its enhancements and the analysis of the MIM opportunity are given in “DOMCT protocol” section. “Simulation results” section shows the simulation results. Finally, we conclude the article and provide our future work in “Conclusion” section.
Various previous studies on the PHY capture effect[9, 16–19] mainly focused on increasing the PHY capture probability. Basically, the PHY capture effect is a coincidental outcome where only one of the collided frames may survive. In contrast, MIM has the capability to capture multiple frames from the collided frames. The authors of[10, 11] thoroughly carried out empirical experiments and quantify the threshold that enables MIM captures. Shuffle[12, 15] implements MAC layer frame scheduling in order to increase MIM concurrent transmissions. However, Shuffle aggressively disables carrier sensing and carries out consecutive concurrent transmissions causing legacy DCF devices to starve. In contrast, DOMCT increases the system throughput via opportunistic concurrent transmissions thus protecting ongoing transmissions of other APs.
A plethora of advanced signal processing mechanisms aim at reducing or eliminating potential interferences[20–22] has been proposed. SIC decodes a relatively stronger signal from overlapped signals and then distracts a weaker signal by subtracting the stronger signal from the overlapped signals. This mechanism requires complex symbol level signal manipulation. Similarly, ZigZag requires signal manipulation to recover the signal from the collided frames. It does not increase the wireless capacity but only reduces the number of retransmissions similar to PPR. On the other hand, IAC, SAM, CSMA/CN support concurrent transmissions by the interference alignment and interference cancellation using multiple signal streams obtainable in MIMO environments. It is worthwhile noting that our proposal, DOMCT, targets single antenna systems.
Some of the centralized architectures[15, 26–30] provide the concurrent transmissions through MAC frame scheduling. However, these mechanisms do not take the MIM functionality into account except for Shuffle. Therefore, they miss the potential concurrency gains from the MIM opportunities. CMAP and OCP support concurrent transmission in a distributed manner. CMAP constructs a conflict map via empirical evaluations and permits concurrent transmissions from exposed terminals. This method is similar to our proposed scheme in the sense that it selectively activates carrier sensing and permits an additional concurrent transmission if it does not corrupt the ongoing frame. However, CMAP makes concurrent transmission decisions based on the historical concurrent transmission results (i.e., success/failure) instead of the explicit SINR-based measurement. OCP also constructs an interference map (IMAP) and conducts concurrent transmission opportunistically. However, as in CMAP, OCP decides the feasibility of concurrent transmissions based on empirical evaluations (i.e., success/failure). In addition, OCP requires changes in the frame structure since it adds a post-amble at the end of the frame.
Assessing the exact interference between contending links is crucial to the system performance because the results of concurrent transmission is tightly coupled with the interference relationship. The authors of[27, 28] introduced an SINR-based conflict map. These schemes are only applicable in a static environment due to large measurement overheads. In contrast, our solution can be operated both in static and mobile environments since we adopt a lightweight online estimation scheme that is similar to micro-probing in constructing the IMAP.
DOMCT consists of two stages. First, an IMAP is constructed by APs to find out the interference relations between the nodes. Then, based on the IMAP, frames are concurrently transmitted when the MIM capture threshold requirements are satisfied.
It is possible that more than one AP may try this operation resulting in collisions or ACK losses. To minimize the collisions among opportunistic APs, each AP estimates the number of neighbor APs and takes a mini-slot back-off at the end of MAC header part of the ongoing frame (line 11). The back-off value is set in proportion to the number of contending APs. We set the range of the mini-slot back-off window as same as the binary exponential back-off window counter. For example, if there are two APs (AP1 and AP2) contending for concurrent transmissions, each AP determines mini-slot back-off counter based on the number of contending APs (e.g., AP1: 1, AP2: 3). AP1 conducts carrier sensing at the first mini-slot and finds it as idle. Thus, AP1 initiates concurrent transmission. AP2 tries to access the medium at the third mini-slot; however, it finds the preamble transmission of AP2, and gives up concurrent transmission. If an ACK frame is lost, we imply it as a concurrent transmission failure. Hence, the AP marks these links as a failed link in the IMAP. Thereafter, it avoids using them in order to protect the transmission of the neighboring APs (line 13–16).
where δ is controlled in proportion to the arrival rate of the traffic volume. The periodic updates (e.g., 1 s) refresh the entire contents in the IMAP. In our simulations, the average update period was measured as 0.64 ms. In addition to the periodic updates, each time an AP conducts a concurrent transmission, the result—e.g., success or failure—is opportunistically updated in the IMAP. Therefore, the IMAP is kept up-to-date and it also copes with time-varying channel and user mobility.
Opportunistic concurrent transmission
DOMCT requires a more sophisticated ACK processing mechanism in the unicast transmission. Even though two frames are delivered successfully, their ACKs can be collided at APs. We avoid ACK collisions by serialized scheduling ACK frames. For example, AP2 knows the ACK transmission time of AP1 by using the MAC header information of AP1’s frame. AP2 avoids overlapping of its own ACK and AP1’s ACK by delaying its ACK transmission until the end of ACK transmission to AP1. Note that our simulation results demonstrate that DOMCT operates well even without ACK serializing, since ACKs are typically transmitted at the basic data rate and the frame length is relatively short. Another possible solution is the piggybacking of SINR reports in the data frames to reduce the adverse effects of ACK collision. Besides ACK collisions, data and ACK frames can collide also. We can avoid this problem making the concurrent transmission completes at the same time the first data transmission finishes.
In this example, we can identify two cases of concurrent transmissions: (i) AP1 → R1 and AP2 → R3 transmissions, and (ii) AP1 → R2 and AP2 → R3. In the first case where AP1 and AP2 are transmitting frames to their corresponding clients R1 and R3 concurrently, both transmissions are successful. As long as AP1 → R1 transmission precedes AP2 → R3 transmission, a concurrent transmission of AP2 does not corrupt AP1’s packet because both frames satisfy the MIM capture threshold requirements (i.e., preceded packet ≥4 dB, followed packet ≥10 dB). On the other hand, in the second case, AP1’s transmission may result in a collision while AP2’s transmission is successful. That is because the SINR at R3 (13 dB) satisfies the MIM capture threshold while the SINR at R2 (1 dB) does not. In this case, AP2 should not transmit in order to protect the transmission from AP1.
Increasing MIM opportunities
In DOMCT, it is important to provide the concurrent transmission opportunities as many as possible to increase the system throughput. We propose a per-station queue strategy and a TR mechanism to supplement the basic operation of DOMCT.
Per-station queue strategy
Let each AP use the per-station queue. If an AP has at least one frame for each client and the MIM capture condition is satisfied then, the per-station queue strategy always enables the concurrent transmission by fetching the appropriate frame from the per-station queue on-the-fly. In Figure 6b, when AP2 overhears the transmission on the link 1 (AP1 → R1), AP2 can fetch a frame to R3. Now, two frames (AP1 → R1, AP2 → R3) can be transmitted concurrently via MIM. Thus, the per-station queue eliminates the blocking problem and increases the concurrent transmission opportunity.
The per-station queue strategy can be regulated depending on the performance criteria such as throughput, delay, or fairness. To increase the throughput, the AP fetches the packet that belongs to the concurrent transmission links from the per-station queue. For a minimum delay, the AP fetches the packet in a FIFO manner. If fairness is the main objective, then the max–min fairness or proportional fairness may be employed. In this article, we choose throughput as an objective metric.
It is necessary to acquire the inter frame transmission time of other APs in order to employ the TR. Thus, the TR can be activated with the persistent traffic such as VoIP and video on-demand (VoD) because the packet generation intervals of these applications are constant or predictable.
MIM opportunity analysis
We observe that the MIM capture occurs frequently as the distance between two APs increases. Moreover, if we consider the case of the reversed transmission order where AP2 initiates a transmission first, the total MIM capture probability will increase substantially. This results show that the MIM capture has a large potential to improve spatial reuse in the current wireless networks, where APs are densely deployed.
We implemented the MIM functions of DOMCT in the ns-2 simulator to compare with the legacy DCF and Shuffle. Note that most of the core functions of Shuffle (e.g., packet reordering) have been implemented. However, for fair comparison, we did not use the block ACK option, since it causes Shuffle-enabled devices to dominate the wireless medium by using consecutive multiple transmissions.
A simple two flows scenario
DOMCT with per-station queue
DOMCT with TR
To see the effect of the TR, we conduct simulations with VoD applications. The inter packet generation time of each VoD session is set to 1200 pkts/s. We varied the number of VoD sessions from 2 to 5 and each AP-STA pair (i.e., one VoD session) is randomly located in a 1 × 1 km2 area. All other settings are the same as described in “Simulation setup” section.
Broadcast and unicast under a mobility scenario
In this section, we study the impact of mobility on DCF, DOMCT, and Shuffle. We further categorize DOMCT into unicast (DOMCT-UC) and broadcast transmissions (DOMCT-BC) in order to study the effect of the ACK packets. We disabled the block ACK option and applied a unicast operation to Shuffle as described in “Simulation setup” section. In these experiments, we used the topology shown in Figure 10a. In the mobile scenario, the APs are fixed while the clients move randomly following the random waypoint mobility model with a random speed, random pause time, and to a random destination.
Performances in a random topology
Until now, we have performed the simulations in small-scale environments. Next, we conduct throughput comparison in a larger random topology.
We varied the number of AP-station pairs from 2 to 25 and each AP-STA pair is randomly located in a 1 × 1 km2. Only the downlink traffic is generated at each AP. We conducted ten runs and the results were averaged.
In this article, we proposed an DOMCT protocol for IEEE 802.11 WLANs to improve the system throughput. DOMCT increases the concurrency by opportunistically transmitting a frame immediately after the MAC header of an ongoing frame if the MIM capture threshold requirements are satisfied. As shown in our ns-2 simulations, DOMCT increases the system throughput by up to 61% higher compared to DCF and achieves close throughput performance compared to Shuffle, the state-of-the-art centralized solution. We are planning to implement DOMCT in a real testbed to verify the feasibility of DOMCT in practice. Also, we will extend DOMCT to be integrated with ad-hoc and mesh networks. We expect DOMCT will enlarge the concurrent transmission chances in ad-hoc and mesh networks since DOMCT is not limited to the downlink traffic only in these networks.
This work was supported in part by the National Research Foundation of Korea(NRF) grant funded by the Korean government(MEST)(No.201208302002) and by the Seoul R&BD Program (WR080951).
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