Analytical handle for ZF reception in distributed massive MIMO

Senanayake, Rajitha; Lozano, Angel; Smith, Peter J.; Evans, Jamie

doi:10.1109/acssc.2016.7868985

Cited by 5 publications

(7 citation statements)

References 16 publications

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“…We note that the instantaneous channel gains of the associated users tend to be larger than those of the interfering nonassociated users. Hence, we approximate the instantaneous channel gains of the non-associated users and unknown channels of the associated users with their expected values [32]. Furthermore, by carefully choosing an appropriate number of pilots, we can ensure that the estimation error remains negligible in comparison to the channel estimates [32].…”

Section: B Zf Receivermentioning

confidence: 99%

“…Hence, we approximate the instantaneous channel gains of the non-associated users and unknown channels of the associated users with their expected values [32]. Furthermore, by carefully choosing an appropriate number of pilots, we can ensure that the estimation error remains negligible in comparison to the channel estimates [32]. As such, we can replace Ω ZF in (20) with its expected value, E[Ω ZF ] = Θ, to obtain an approximation as…”

Section: B Zf Receivermentioning

confidence: 99%

“…Therefore, when R = Θ − 1 2 ( Ĥ0 ) n and β = 0, E[X] can be expressed as a diagonal matrix. We also note that X is an idempotent matrix (Appendix B) and therefore the trace of X is equal to its rank [32]. Accordingly, following a similar approach to [21], we approximate X by a simple diagonal matrix as…”

Section: Lemmamentioning

confidence: 99%

See 2 more Smart Citations

Zeroing Unknown Terms: A Novel Clustering Architecture for Low Network Overhead in Distributed Massive MIMO

Gunasekara,

Senanayake,

Smith

et al. 2024

IEEE Open J. Commun. Soc.

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We propose a novel user-centric clustering architecture for distributed massive multiple-inputmultiple-output networks. We examine the uplink of a general multi-cell scenario in which a cluster of base stations (BSs) with large antenna arrays detect the signals of multiple users simultaneously. As opposed to traditional clustering schemes, where the channel coefficients of all the users within the cooperating cluster are learned at the BSs, in the proposed approach, BSs in the network learn the channels of only the strongest users based on the received signal-to-noise ratio. We consider two linear receivers, namely, zero forcing and linear minimum mean squared error receivers at the central processing unit. The two receivers operate with only partial knowledge of the user channels and the unknown terms are set to zero. We conduct a thorough analytical investigation and derive novel approximations for the instantaneous received signal-to-interference-and-noise ratio of an arbitrary user processed by a cluster of BSs. Furthermore, we develop simple closed-form expressions for the achievable rate and symbol error probability of an arbitrary user processed by a cluster of BSs. Numerical examples are used to illustrate the accuracy of the proposed approach and also to compare it to existing approaches. We show that our proposed architecture outperforms traditional clustering methods, particularly for cluster edge users.

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Section: B Zf Receivermentioning

confidence: 99%

Section: B Zf Receivermentioning

confidence: 99%

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Zeroing Unknown Terms: A Novel Clustering Architecture for Low Network Overhead in Distributed Massive MIMO

Gunasekara,

Senanayake,

Smith

et al. 2024

IEEE Open J. Commun. Soc.

Self Cite

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“…Progress in distributed antenna systems has also been tremendous during the past five years, see e.g., [132][133][134][135][136][137][138][139] and references therein. The concept of cell-free massive MIMO has been pointed out as a promising way to realize distributed antenna systems below 6 GHz which can scale to large physical areas.…”

Section: New Physical Layer Techniques For 6gmentioning

confidence: 99%

6G Wireless Systems: Vision, Requirements, Challenges, Insights, and Opportunities

Tataria¹,

Shafi²,

Molisch³

et al. 2020

Preprint

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Mobile communications have been undergoing a generational change every ten years or so. However, the time difference between the so-called "G's" is also decreasing. While fifth-generation (5G) systems are becoming a commercial reality, there is already significant interest in systems beyond 5G -which we refer to as the sixth-generation (6G) of wireless systems. In contrast to the many published papers on the topic, we take a top-down approach to 6G. More precisely, we present a holistic discussion of 6G systems beginning with the lifestyle and societal changes driving the need for next generation networks, to the technical requirements needed to enable 6G applications, through to the challenges, as well as possibilities for practically realizable system solutions across all layers of the Open Systems Interconnection stack (i.e., from application to the physical layer). Since many of the 6G applications will need access to an orderof-magnitude more spectrum, utilization of frequencies between 100 GHz and 1 THz becomes of paramount importance. As such, the 6G eco-system will feature a diverse range of frequencies, ranging from below 6 GHz up to 1 THz. We comprehensively characterize the limitations that must be overcome to realize working systems in these bands; and provide a unique perspective on the physical, as well as higher layer challenges relating to the design of next generation core networks, new modulation and coding methods, novel multiple access techniques, antenna arrays, wave propagation, radio-frequency transceiver design, as well as real-time signal processing. We rigorously discuss the fundamental changes required in the core networks of the future, such as the redesign or significant reduction of the transport architecture that serves as a major source of latency for timesensitive applications. This is in sharp contrast to the present hierarchical network architectures, which are not suitable to realize many of the anticipated 6G services. While evaluating the strengths and weaknesses of key candidate 6G technologies, we differentiate what may be practically achievable over the next decade, relative to what is possible in theory. Keeping this in mind, we present concrete research challenges for each of the discussed system aspects, providing inspiration for what follows.

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“…To obtain the SINR expression for our quantized CF massive MIMO we follow the approximation derived in [9]. We applŷ G in our zero forcing detector to detect the data from (35) and apply a filter Λ −1/2 to r d to whiten z, such that we have a ZF detector matrix…”

Section: A Channel Modelmentioning

confidence: 99%

On the Uplink Throughput of Zero Forcing in Cell-Free Massive MIMO With Coarse Quantization

Maryopi

Bashar

Burr

2019

IEEE Trans. Veh. Technol.

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The recently proposed Cell-Free massive MIMO architecture is studied for the uplink. In contrast to most previous works, joint detection is performed using global CSI. Therefore, we study strategies for transferring CSI to the CPU taking into account the fronthaul capacity which limits CSI quantization. Two strategies for pilot-based CSI acquisition are considered: estimate-and-quantize and quantize-and-estimate. These are analysed using the Bussgang decomposition. For a given quantization constraint for the data and CSI the achievable rate per user with Zero-Forcing is determined. Numerical results show that quantize-and-estimate (the simpler strategy) is similar to or better than estimate-and-quantize at low resolution, especially for 1-bit.

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Analytical handle for ZF reception in distributed massive MIMO

Cited by 5 publications

References 16 publications

Zeroing Unknown Terms: A Novel Clustering Architecture for Low Network Overhead in Distributed Massive MIMO

Zeroing Unknown Terms: A Novel Clustering Architecture for Low Network Overhead in Distributed Massive MIMO

6G Wireless Systems: Vision, Requirements, Challenges, Insights, and Opportunities

On the Uplink Throughput of Zero Forcing in Cell-Free Massive MIMO With Coarse Quantization

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