A coalitional game-inspired algorithm for resource allocation in orthogonal frequency division multiple access

Shams, Farshad; Bacci, Giacomo; Luise, Marco

doi:10.1109/ew.2010.5483424

Cited by 1 publication

(4 citation statements)

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“…Since the nodes can be selfish (i.e., to maximize their payoffs, they may set the backoff windows to be the smallest value), a penalizing mechanism is required for the misbehaving nodes. [28] TDMA cognitive radio minus a function of transmission delay Time slot allocation [29] Repeated game Mobile nodes Power allocated Long-term throughput Nash equilibrium to each time slot Time slot allocation [29] Repeated game with Mobile nodes Channel gain Transmission rate plus Nash equilibrium incomplete information to each time slot transfer function Channel allocation [30] Noncooperative game Mobile nodes with The number of radios assigned Throughput minus cost Strongly dominantmultiple radios to each channel strategy equilibrium Sub-channel allocation [32] Noncooperative game Mobile nodes Rate assigned to each sub-channel Transmission power minimization Nash equilibrium Channel allocation [33] Noncooperative game Mobile nodes with The number of radio assigned Achieve bit rate Nash equilibrium multiple radios to each channel Sub-channel and Noncooperative game Base stations Transmission power and sub-channel Data rate Nash equilibrium power allocations [34] assigned to mobile nodes Channel allocation [35] Noncooperative game Secondary nodes Channel selection Function of SINR Nah equilibrium Channel allocation [35] Stackelberg game Secondary nodes Channel selection Function of SINR and Nash equilibrium cost of switching channel Transmission power allocation [36] Auction game Mobile nodes and a base station Power control variable Shannon capacity Nash equilibrium and bid value Cooperative group formation [38] Coalitional game Secondary base stations Coalition's member selection Utility from learning new channels Nash equilibrium in multi-channel network minus cost of cooperation (Nash-stable formation) Sub-channel assignment and [40] Coalitional game Mobile nodes Transmission power assigned Function of ShannonNash equilibrium power allocation to each channel capacity Power control in CDMA [41] Noncooperative game Mobile nodes Transmission power selection Fraction of throughput Nash equilibrium to transmission power Power control in CDMA [42] Bayesian game Mobile nodes Transmission power selection Difference between Bayesian Nash equilibrium throughput and power consumption Power control in CDMA [43] Noncooperative game Mobile nodes Transmission power selection Difference between throughput Nash equilibrium (bits/second) and cost of transmission power Joint rate and power Noncooperative game Mobile nodes Transmission power and Utility in Nash equilibrium control in CDMA [44], [46] rate selections bits/J Power control in CDMA [47] Noncooperative game Mobile nodes Transmission power selection cost a function of Nash equilibrium power and SIR ...…”

Section: B Open Research Issuesmentioning

confidence: 99%

“…to update best-responses based on Markov modeling [40] be obtained. The definition of the dual game is as follows:…”

Section: B Channel Access Games In Fdmamentioning

confidence: 99%

“…A distributed algorithm to find a Nash-stable partition is proposed and the simulation results show that the average payoff per SBS of the coalition formation scheme outperforms one of the noncooperative schemes when the number of SBS increases. Another coalitional game for transmission power allocation and subchannel assignment in the uplink channel of an OFDMA system is presented in [40]. In the considered system model, there are M nodes located in the coverage area of a same base station.…”

Section: B Channel Access Games In Fdmamentioning

confidence: 99%

“…3. Coalitions of players are formed following the game model in [40] when there are 3 mobile nodes and 3 subchannels.…”

Section: B Channel Access Games In Fdmamentioning

confidence: 99%

See 3 more Smart Citations

Game Theoretic Approaches for Multiple Access in Wireless Networks: A Survey

Akkarajitsakul

Hossain

Niyato

et al. 2011

IEEE Commun. Surv. Tutorials

219

118

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Multiple access methods in a wireless network allow multiple nodes to share a set of available channels for data transmission. The nodes can either compete or cooperate with each other to access the channel(s) so that either an individual or a group objective can be achieved. Game theory, which is a mathematical tool developed to understand the interaction among rational entities, can be applied to model and to analyze individual or group behaviour of nodes for multiple access in wireless networks. Game theory also enables us to model the selfish/malicious behaviour of nodes, and subsequently design the punishment or defense mechanisms for robust multiple access in wireless networks. In addition, game models can provide distributed solutions to the multiple access problems, which are based on solid theoretical foundations. In this survey, we provide a comprehensive review of the game models (e.g., noncooperative/cooperative, static/dynamic, and complete/incomplete information) developed for different multiple access schemes (i.e., contention-free and contention-based random channel access) in wireless networks. We consider time-division multiple access (TDMA), frequency-division multiple access (FDMA), and codedivision multiple access (CDMA), ALOHA, and carrier sense multiple access (CSMA)-based wireless networks. In addition, game models for multiple access in dynamic spectrum accessbased cognitive radio networks are reviewed. The major findings from the game models used for these different access schemes are highlighted. To this end, several of the key open research directions are outlined.Index Terms-Wireless networks, game theory, multiple access, random access game, power and rate control game.

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