Superposition coding for wireless mesh networks

Li, Li; Alimi, Richard; Ramjee, Ramachandran; Shi, Jingpu; Sun, Yanjun; Viswanathan, Harish; Yang, Yang Richard

doi:10.1145/1287853.1287897

Cited by 25 publications

(22 citation statements)

References 4 publications

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“…Interestingly, when the transmission set size is bounded to 2 (K = 2), under reasonable assumptions regarding the maximum achievable SINR during transmission of two messages, there exist exact polynomial-time algorithms to solve SSC which are presented next. We note that this case is important in practice as in most implementations, SC is limited to transmission of 2 packets [3], [12] due to aforementioned physical constraints.…”

Section: A Integer Programming Solutionmentioning

confidence: 99%

“…The delay region is defined as the set of all delay vectors achievable by a scheduling algorithm when there are no further packet arrival in the system. Moreover, in [12] a practical design of a SCenabled MAC scheduler was presented where the objective was to optimize throughput. An experimental implementation and evaluation of SC using software-define radio was presented in [13].…”

Section: Introductionmentioning

confidence: 99%

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Minimum delay scheduling with multi-packet transmission in wireless networks

Abbasi

Ghaderi

2015

2015 IEEE 16th International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM)

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Abstract-This paper studies the problem of minimum delay scheduling in wireless networks with multi-packet transmission capability. Specifically, we assume that the network employs superposition coding at the physical layer in order to implement multi-packet transmission. While most studies on superposition coding assume that unbounded number of packets can be coded together, physical and MAC layer limitations restrict the number of concurrent packets in a transmission set. Taking this constraint into consideration, we formulate the minimum delay scheduling as a combinatorial optimization problem and study its computational complexity under different transmission set sizes. We show that, when the transmission set size is limited to 2 packets, the problem can be solved optimally in polynomial time. Moreover, while the complexity of the problem for larger transmission set sizes is unknown, we present close-to-optimal heuristic algorithms that compute efficient solutions for the problem in polynomial time. Numerical results are also presented to study the efficiency and utility of the presented scheduling algorithms. Our results show that the heuristic algorithms are highly efficient, achieving delays that are less than 2% away from the optimal values.

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Section: A Integer Programming Solutionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Minimum delay scheduling with multi-packet transmission in wireless networks

Abbasi

Ghaderi

2015

2015 IEEE 16th International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM)

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“…Thus, non-SPC and SPC signals originating from other nodes are treated as noise and cannot be canceled out. There is also some interesting work that focuses on the design of practical networks using SPC [22]. Here, the first design of a practical medium access protocol with SPC is presented for wireless mesh networks and average gains in the range of 10% to 20% are reported with respect to the standard 802.11 protocol.…”

Section: B Related Workmentioning

confidence: 99%

Cross-Layer Optimization Using Advanced Physical Layer Techniques in Wireless Mesh Networks

Shabdanov

Mitran

Rosenberg

2012

IEEE Trans. Wireless Commun.

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Abstract-The objective of this paper is to study the impact of advanced physical layer techniques on the maximum achievable throughput of wireless multihop mesh networks. We formulate a cross-layer optimization framework for the routing and scheduling problem jointly with the following physical layer techniques: successive interference cancellation, superposition coding, dirtypaper coding and their combinations. In the case when each node is enabled with superposition coding, we need to formulate a power allocation subproblem for the optimal power partition of the superimposed signals. We solve these joint problems exactly to compute the maximum achievable throughput in realistic size networks. This allows us to quantify the performance gains obtained by using these techniques (and their combinations). Specifically, we find that the use of dirty-paper coding (only at the gateway) is not justified in networks with mixed uplink and downlink flows. On the other hand, the combination of superposition coding with successive interference outperforms significantly other techniques across all transmission power range for both uplink and downlink flows. We also provide a number of interesting practical insights on throughput improvement by comparing different combinations of these techniques.

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“…SIC can be employed for both uplink [5] and downlink [6] transmissions. However, at the uplink direction, SIC is able to achieve a higher throughput since the total received power is higher.…”

Section: Introductionmentioning

confidence: 99%

Fair and efficient scheduling in wireless networks with successive interference cancellation

Mollanoori

Ghaderi

2011

2011 IEEE Wireless Communications and Networking Conference

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Abstract-This paper considers the problem of uplink scheduling in wireless networks supporting successive interference cancellation (SIC) at the physical layer. By allowing concurrent interfering transmissions, SIC enables multi-packet reception at the receiver resulting in increased network throughput. Specifically, we consider maximum throughput scheduling and proportional fair scheduling problems and study optimal and heuristic algorithms for these problems. We prove that the maximum throughput scheduling problem is NP-hard and develop a throughput efficient polynomial time greedy algorithm for the problem. While being throughput efficient, the maximum throughput scheduling can lead to highly unfair rates among the users. The proportional fair scheduling, on the other hand, is not throughput optimal but achieves proportional fairness among the users. For scheduling multiple users in a single time-slot, we show that there exists an algorithm that solves the proportional fair scheduling problem in polynomial time. For scheduling in multiple time-slots, we develop a greedy algorithm that computes a highly fair schedule in polynomial time. Numerical results are also provided to show the utility and efficiency of the proposed scheduling algorithms in various simulated networks.

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Superposition coding for wireless mesh networks

Cited by 25 publications

References 4 publications

Minimum delay scheduling with multi-packet transmission in wireless networks

Minimum delay scheduling with multi-packet transmission in wireless networks

Cross-Layer Optimization Using Advanced Physical Layer Techniques in Wireless Mesh Networks

Fair and efficient scheduling in wireless networks with successive interference cancellation

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