Superposition Coding Strategies: Design and Experimental Evaluation

Vanka, S.; Srinivasa, Sunil; Gong, Zhangbin; Vizi, P. G.; Stamatiou, Kostas; Haenggi, Martin

doi:10.1109/twc.2012.051512.111622

Cited by 164 publications

(119 citation statements)

References 13 publications

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“…I(X 1 ; W|H) ≥ I(X 1 ; Y|H). As a consequence, superposing X 2 H over W (11) results in no more capacity in comparison with the case where only X 1 is transmitted (12). Hence, the capacity of user 1 in the MU coherent setup is never higher than in the SU coherent setup.…”

Section: Downlink Non-coherent Multi-user Gainmentioning

confidence: 99%

“…Following the rationale of [11], in the Gaussian broadcast channel with multiple receivers, superposing messages with different power levels generally improves the achievable rates in comparison with time sharing procedures, provided that successive decoding at the receivers is feasible [12]. With the aim of validating this conclusion under non-coherent detection, in this work we combine superposition coding [11] with GC, i.e.…”

Section: System Modelmentioning

confidence: 99%

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Multi-User Non-Coherent Detection for Downlink MIMO Communication

Roger

Calabuig

Cabrejas

et al. 2014

IEEE Signal Process. Lett.

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Current cellular technologies are based on the concept of coherent communication, in which the channel matrix used for demodulation is estimated via reference or pilot signals. Coherent systems, however, involve a significant increase of the signalling overhead, especially when the number of transmission points is increased or when the mobile channel changes rapidly, which motivates the use of non-coherent techniques. This letter extends the use of non-coherent communications to a multi-user (MU) multiple-input multiple-output (MIMO) framework by combining superposition coding with a reduced-complexity detection method. Numerical results confirm that our scheme achieves higher user rates than non-coherent MU transmission based on time multiplexing. In addition to the well-known sumrate gain of MU systems, an extra performance gain given by downlink non-coherent MU communication is shown and qualitatively justified.

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Section: Downlink Non-coherent Multi-user Gainmentioning

confidence: 99%

Section: System Modelmentioning

confidence: 99%

Multi-User Non-Coherent Detection for Downlink MIMO Communication

Roger

Calabuig

Cabrejas

et al. 2014

IEEE Signal Process. Lett.

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“…2 with the fact that the marks {t i } are independent from Ξ. More precisely, when θ ≥ 1 (SMUD Regime), it is not possible for the UE to decode any BS other than the strongest BS without SIC 11 . Thus, the coverage probability without SIC is the product of the probability that the strongest BS being accessible η and the probability of decoding the strongest BS p 1 .…”

Section: ) Without Sicmentioning

confidence: 99%

“…In particular, based on Prop. 2, a lower bound can be 11 Intuitively, decoding any BS weaker than the strongest BS implies that this BS is stronger than the strongest BS and causes contradiction. This argument can be made rigorous by applying Lemma 10 (in App.…”

Section: Proposition 13 In the K-tier Heterogeneous Cellular Networkmentioning

confidence: 99%

The performance of successive interference cancellation in random wireless networks

Zhang

Haenggi

2012

2012 IEEE Global Communications Conference (GLOBECOM)

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This paper provides a unified framework to study the performance of successive interference cancellation (SIC) in wireless networks with arbitrary fading distribution and power-law path loss.An analytical characterization of the performance of SIC is given as a function of different system parameters. The results suggest that the marginal benefit of enabling the receiver to successively decode k users diminishes very fast with k, especially in networks of high dimensions and small path loss exponent. On the other hand, SIC is highly beneficial when the users are clustered around the receiver and/or very low-rate codes are used. Also, with multiple packet reception, a lower per-user information rate always results in higher aggregate throughput in interference-limited networks. In contrast, there exists a positive optimal per-user rate that maximizes the aggregate throughput in noisy networks.The analytical results serve as useful tools to understand the potential gain of SIC in heterogeneous cellular networks (HCNs). Using these tools, this paper quantifies the gain of SIC on the coverage probability in HCNs with non-accessible base stations. An interesting observation is that, for contemporary narrow-band systems (e.g., LTE and WiFi), most of the gain of SIC is achieved by canceling a single interferer.

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“…With recent advances in multi-user signal processing, the implementation of multi-packet transmission and reception is advancing rapidly. Indeed, software-defined radio implementations of multi-packet reception and transmission have been reported in the literature [2], [3]. Such techniques increase the network capacity substantially by decoding the otherwise colliding packets.…”

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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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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Superposition Coding Strategies: Design and Experimental Evaluation

Cited by 164 publications

References 13 publications

Multi-User Non-Coherent Detection for Downlink MIMO Communication

Multi-User Non-Coherent Detection for Downlink MIMO Communication

The performance of successive interference cancellation in random wireless networks

Minimum delay scheduling with multi-packet transmission in wireless networks

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